diff --git a/Code/ExecClassif.py b/Code/MonoMutliViewClassifiers/ExecClassif.py
similarity index 62%
rename from Code/ExecClassif.py
rename to Code/MonoMutliViewClassifiers/ExecClassif.py
index dab41d2a8884f06ad89ef53c16c7501cbdb145fa..2a02e7dd843b3ac8a000ce9012cb3cf91a0479b8 100644
--- a/Code/ExecClassif.py
+++ b/Code/MonoMutliViewClassifiers/ExecClassif.py
@@ -11,6 +11,8 @@ import logging
from joblib import Parallel, delayed
from ResultAnalysis import resultAnalysis
import numpy as np
+import MonoviewClassifiers
+
parser = argparse.ArgumentParser(
description='This file is used to benchmark the accuracies fo multiple classification algorithm on multiview data.',
@@ -62,12 +64,26 @@ groupRF = parser.add_argument_group('Random Forest arguments')
groupRF.add_argument('--CL_RF_trees', metavar='STRING', action='store', help='GridSearch: Determine the trees',
default='25 75 125 175')
-groupSVC = parser.add_argument_group('SVC arguments')
-groupSVC.add_argument('--CL_SVC_kernel', metavar='STRING', action='store', help='GridSearch : Kernels used',
- default='linear')
-groupSVC.add_argument('--CL_SVC_C', metavar='STRING', action='store', help='GridSearch : Penalty parameters used',
+groupSVMLinear = parser.add_argument_group('Linear SVM arguments')
+groupSVMLinear.add_argument('--CL_SVML_C', metavar='STRING', action='store', help='GridSearch : Penalty parameters used',
default='1:10:100:1000')
+groupSVMRBF = parser.add_argument_group('SVW-RBF arguments')
+groupSVMRBF.add_argument('--CL_SVMR_C', metavar='STRING', action='store', help='GridSearch : Penalty parameters used',
+ default='1:10:100:1000')
+
+groupSVMPoly = parser.add_argument_group('Poly SVM arguments')
+groupSVMPoly.add_argument('--CL_SVMP_C', metavar='STRING', action='store', help='GridSearch : Penalty parameters used',
+ default='1:10:100:1000')
+groupSVMPoly.add_argument('--CL_SVMP_deg', metavar='STRING', action='store', help='GridSearch : Degree parameters used',
+ default='1:2:5:10')
+
+groupAdaboost = parser.add_argument_group('Adaboost arguments')
+groupAdaboost.add_argument('--CL_Ada_n_est', metavar='STRING', action='store', help='GridSearch : Penalty parameters used',
+ default='1:10:100:1000')
+groupAdaboost.add_argument('--CL_Ada_b_est', metavar='STRING', action='store', help='GridSearch : Degree parameters used',
+ default='DecisionTreeClassifier')
+
groupRF = parser.add_argument_group('Decision Trees arguments')
groupRF.add_argument('--CL_DT_depth', metavar='STRING', action='store',
help='GridSearch: Determine max depth for Decision Trees', default='1:3:5:7')
@@ -90,8 +106,9 @@ groupMumbo.add_argument('--MU_types', metavar='STRING', action='store',
groupMumbo.add_argument('--MU_config', metavar='STRING', action='store', nargs='+',
help='Configuration for the monoview classifier in Mumbo',
default=['3:1.0', '3:1.0', '3:1.0','3:1.0'])
-groupMumbo.add_argument('--MU_iter', metavar='INT', action='store',
- help='Number of iterations in Mumbos learning process', type=int, default=5)
+groupMumbo.add_argument('--MU_iter', metavar='INT', action='store', nargs=3,
+ help='Max number of iteration, min number of iteration, convergence threshold', type=float,
+ default=[1000, 300, 0.0005])
groupFusion = parser.add_argument_group('Fusion arguments')
groupFusion.add_argument('--FU_types', metavar='STRING', action='store',
@@ -151,16 +168,17 @@ if args.CL_type.split(":")==["Benchmark"]:
for fusionModulesName, fusionModule in zip(fusionModulesNames, fusionModules)]
fusionMethods = dict((fusionModulesName, [subclass.__name__ for subclass in fusionClasse.__subclasses__() ])
for fusionModulesName, fusionClasse in zip(fusionModulesNames, fusionClasses))
- fusionMonoviewClassifiers = [name for _, name, isPackage in
- pkgutil.iter_modules(['Multiview/Fusion/Methods/MonoviewClassifiers'])
- if not isPackage ]
+ allMonoviewAlgos = [name for _, name, isPackage in
+ pkgutil.iter_modules(['MonoviewClassifiers'])
+ if not isPackage]
+ fusionMonoviewClassifiers = allMonoviewAlgos
allFusionAlgos = {"Methods": fusionMethods, "Classifiers": fusionMonoviewClassifiers}
allMumboAlgos = [name for _, name, isPackage in
pkgutil.iter_modules(['Multiview/Mumbo/Classifiers'])
if not isPackage and not name in ["SubSampling", "ModifiedMulticlass", "Kover"]]
allMultiviewAlgos = {"Fusion": allFusionAlgos, "Mumbo": allMumboAlgos}
- allMonoviewAlgos = [key[15:] for key in dir(Monoview.ClassifMonoView) if key[:15] == "MonoviewClassif"]
benchmark = {"Monoview": allMonoviewAlgos, "Multiview" : allMultiviewAlgos}
+
if "Multiview" in args.CL_type.strip(":"):
benchmark["Multiview"] = {}
if "Mumbo" in args.CL_algos_multiview.split(":"):
@@ -178,138 +196,98 @@ if "Multiview" in args.CL_type.strip(":"):
if "Monoview" in args.CL_type.strip(":"):
benchmark["Monoview"] = args.CL_algos_monoview.split(":")
+
classifierTable = "a"
fusionClassifierConfig = "a"
fusionMethodConfig = "a"
mumboNB_ITER = 2
mumboClassifierConfig = "a"
mumboclassifierNames = "a"
-RandomForestKWARGS = {"classifier__n_estimators":map(int, args.CL_RF_trees.split())}
-SVCKWARGS = {"classifier__kernel":args.CL_SVC_kernel.split(":"), "classifier__C":map(int,args.CL_SVC_C.split(":"))}
-DecisionTreeKWARGS = {"classifier__max_depth":map(int,args.CL_DT_depth.split(":"))}
-SGDKWARGS = {"classifier__alpha" : map(float,args.CL_SGD_alpha.split(":")), "classifier__loss":args.CL_SGD_loss.split(":"),
- "classifier__penalty":args.CL_SGD_penalty.split(":")}
-KNNKWARGS = {"classifier__n_neighbors": map(float,args.CL_KNN_neigh.split(":"))}
-
-
-argumentDictionaries = {"Monoview":{}, "Multiview":[]}
-# if benchmark["Monoview"]:
-# for view in args.views.split(":"):
-# argumentDictionaries["Monoview"][str(view)] = []
-# for classifier in benchmark["Monoview"]:
-# arguments = {classifier+"KWARGS": globals()[classifier+"KWARGS"], "feat":view, "fileFeat": args.fileFeat,
-# "fileCL": args.fileCL, "fileCLD": args.fileCLD, "CL_type": classifier,
-# classifier+"KWARGS": globals()[classifier+"KWARGS"]}
-# argumentDictionaries["Monoview"][str(view)].append(arguments)
-#
-# bestClassifiers = []
-# bestClassifiersConfigs = []
-# for viewIndex, viewArguments in enumerate(argumentDictionaries["Monoview"].values()):
-# resultsMonoview = Parallel(n_jobs=nbCores)(
-# delayed(ExecMonoview)(DATASET.get("View"+str(viewIndex)).value, DATASET.get("labels").value, args.name,
-# args.CL_split, args.CL_nbFolds, 1, args.type, args.pathF, gridSearch=True,
-# **arguments)
-# for arguments in viewArguments)
-# accuracies = [result[1] for result in resultsMonoview]
-# classifiersNames = [result[0] for result in resultsMonoview]
-# classifiersConfigs = [result[2] for result in resultsMonoview]
-# bestClassifiers.append(classifiersNames[np.argmax(np.array(accuracies))])
-# bestClassifiersConfigs.append(classifiersConfigs[np.argmax(np.array(accuracies))])
-bestClassifiers = ["DecisionTree", "DecisionTree", "DecisionTree", "DecisionTree"]
-bestClassifiersConfigs = [["1"],["1"],["1"],["1"]]
+
+RandomForestKWARGS = {"0":map(int, args.CL_RF_trees.split())}
+SVMLinearKWARGS = {"0":map(int, args.CL_SVML_C.split(":"))}
+SVMRBFKWARGS = {"0":map(int, args.CL_SVMR_C.split(":"))}
+SVMPolyKWARGS = {"0":map(int, args.CL_SVMP_C.split(":")), '1':map(int, args.CL_SVMP_deg.split(":"))}
+DecisionTreeKWARGS = {"0":map(int, args.CL_DT_depth.split(":"))}
+SGDKWARGS = {"0": map(float, args.CL_SGD_alpha.split(":")), "1":args.CL_SGD_loss.split(":"),
+ "2": args.CL_SGD_penalty.split(":")}
+KNNKWARGS = {"0": map(float, args.CL_KNN_neigh.split(":"))}
+AdaboostKWARGS = {"0": args.CL_Ada_n_est.split(":"), "1": args.CL_Ada_b_est.split(":")}
+
+
+argumentDictionaries = {"Monoview": {}, "Multiview": []}
+if benchmark["Monoview"]:
+ for view in args.views.split(":"):
+ argumentDictionaries["Monoview"][str(view)] = []
+ for classifier in benchmark["Monoview"]:
+
+ arguments = {classifier+"KWARGS": globals()[classifier+"KWARGS"], "feat":view, "fileFeat": args.fileFeat,
+ "fileCL": args.fileCL, "fileCLD": args.fileCLD, "CL_type": classifier}
+
+ argumentDictionaries["Monoview"][str(view)].append(arguments)
+bestClassifiers = []
+bestClassifiersConfigs = []
+for viewIndex, viewArguments in enumerate(argumentDictionaries["Monoview"].values()):
+ resultsMonoview = Parallel(n_jobs=nbCores)(
+ delayed(ExecMonoview)(DATASET.get("View"+str(viewIndex)).value, DATASET.get("labels").value, args.name,
+ args.CL_split, args.CL_nbFolds, 1, args.type, args.pathF, gridSearch=True,
+ **arguments)
+ for arguments in viewArguments)
+
+ accuracies = [result[1] for result in resultsMonoview]
+ classifiersNames = [result[0] for result in resultsMonoview]
+ classifiersConfigs = [result[2] for result in resultsMonoview]
+ bestClassifiers.append(classifiersNames[np.argmax(np.array(accuracies))])
+ bestClassifiersConfigs.append(classifiersConfigs[np.argmax(np.array(accuracies))])
+# bestClassifiers = ["DecisionTree", "DecisionTree", "DecisionTree", "DecisionTree"]
+# bestClassifiersConfigs = [["1"],["1"],["1"],["1"]]
+
if benchmark["Multiview"]:
+ if benchmark["Multiview"]["Mumbo"]:
+ for classifier in benchmark["Multiview"]["Mumbo"]:
+ arguments = {"CL_type": "Mumbo",
+ "views": args.views.split(":"),
+ "NB_VIEW": len(args.views.split(":")),
+ "NB_CLASS": len(args.CL_classes.split(":")),
+ "LABELS_NAMES": args.CL_classes.split(":"),
+ "MumboKWARGS": {"classifiersNames": ["DecisionTree", "DecisionTree", "DecisionTree",
+ "DecisionTree"],
+ "maxIter":int(args.MU_iter[0]), "minIter":int(args.MU_iter[1]),
+ "threshold":args.MU_iter[2]}}
+ argumentDictionaries["Multiview"].append(arguments)
if benchmark["Multiview"]["Fusion"]:
if benchmark["Multiview"]["Fusion"]["Methods"]["LateFusion"] and benchmark["Multiview"]["Fusion"]["Classifiers"]:
for method in benchmark["Multiview"]["Fusion"]["Methods"]["LateFusion"]:
- arguments = {"CL_type": "Fusion",
- "views": args.views.split(":"),
- "NB_VIEW": len(args.views.split(":")),
- "NB_CLASS": len(args.CL_classes.split(":")),
- "LABELS_NAMES": args.CL_classes.split(":"),
- "FusionKWARGS": {"fusionType":"LateFusion", "fusionMethod":method,
- "classifiersNames": bestClassifiers,
- "classifiersConfigs": bestClassifiersConfigs,
- 'fusionMethodConfig': fusionMethodConfig},
- "MumboKWARGS":""}
- argumentDictionaries["Multiview"].append(arguments)
+ arguments = {"CL_type": "Fusion",
+ "views": args.views.split(":"),
+ "NB_VIEW": len(args.views.split(":")),
+ "NB_CLASS": len(args.CL_classes.split(":")),
+ "LABELS_NAMES": args.CL_classes.split(":"),
+ "FusionKWARGS": {"fusionType":"LateFusion", "fusionMethod":method,
+ "classifiersNames": bestClassifiers,
+ "classifiersConfigs": bestClassifiersConfigs,
+ 'fusionMethodConfig': fusionMethodConfig}}
+ argumentDictionaries["Multiview"].append(arguments)
if benchmark["Multiview"]["Fusion"]["Methods"]["EarlyFusion"] and benchmark["Multiview"]["Fusion"]["Classifiers"]:
for method in benchmark["Multiview"]["Fusion"]["Methods"]["EarlyFusion"]:
for classifier in benchmark["Multiview"]["Fusion"]["Classifiers"]:
arguments = {"CL_type": "Fusion",
- "views": args.views.split(":"),
- "NB_VIEW": len(args.views.split(":")),
- "NB_CLASS": len(args.CL_classes.split(":")),
- "LABELS_NAMES": args.CL_classes.split(":"),
- "FusionKWARGS": {"fusionType":"EarlyFusion", "fusionMethod":method,
- "classifiersNames": classifier,
- "classifiersConfigs": fusionClassifierConfig,
- 'fusionMethodConfig': fusionMethodConfig},
- "MumboKWARGS":""}
+ "views": args.views.split(":"),
+ "NB_VIEW": len(args.views.split(":")),
+ "NB_CLASS": len(args.CL_classes.split(":")),
+ "LABELS_NAMES": args.CL_classes.split(":"),
+ "FusionKWARGS": {"fusionType":"EarlyFusion", "fusionMethod":method,
+ "classifiersNames": classifier,
+ "classifiersConfigs": fusionClassifierConfig,
+ 'fusionMethodConfig': fusionMethodConfig}}
argumentDictionaries["Multiview"].append(arguments)
- if benchmark["Multiview"]["Mumbo"]:
- #for classifier in benchmark["Multiview"]["Mumbo"]:
- for i in range(int(np.power(len(args.views.split(":")), len(benchmark["Multiview"]["Mumbo"])))):
- arguments = {"CL_type": "Mumbo",
- "views": args.views.split(":"),
- "NB_VIEW": len(args.views.split(":")),
- "NB_CLASS": len(args.CL_classes.split(":")),
- "LABELS_NAMES": args.CL_classes.split(":"),
- "MumboKWARGS": {"classifiersConfigs": mumboClassifierConfig,"NB_ITER": mumboNB_ITER,
- "classifiersNames": ["DecisionTree", "DecisionTree", "DecisionTree", "DecisionTree"]},
- "FusionKWARGS": ""}
- argumentDictionaries["Multiview"].append(arguments)
resultsMultiview = Parallel(n_jobs=nbCores)(
delayed(ExecMultiview)(DATASET, args.name, args.CL_split, args.CL_nbFolds, 1, args.type, args.pathF,
LABELS_DICTIONARY, gridSearch=True, **arguments)
for arguments in argumentDictionaries["Multiview"])
-# for classifierType, argumentsList in argumentDictionaries.iteritems():
-# executionMethod = globals()["Exec"+classifierType]
-# results[classifierType] = Parallel(n_jobs=args.CL_cores)(delayed(executionMethod)
-# (args.name, args.CL_split,args.CL_nbFolds, 1, args.type,
-# args.pathF, **arguments)
-# for arguments in argumentsList)
resultAnalysis(benchmark, results)
print len(argumentDictionaries["Multiview"]), len(argumentDictionaries["Monoview"])
-
-# views = args.views.split(":")
-# dataBaseType = args.type
-# NB_VIEW = len(views)
-# mumboClassifierConfig = [argument.split(':') for argument in args.MU_config]
-#
-# LEARNING_RATE = args.CL_split
-# nbFolds = args.CL_nbFolds
-# NB_CLASS = args.CL_nb_class
-# LABELS_NAMES = args.CL_classes.split(":")
-# mumboclassifierNames = args.MU_type.split(':')
-# mumboNB_ITER = args.MU_iter
-# NB_CORES = args.CL_cores
-# fusionClassifierNames = args.FU_cl_names.split(":")
-# fusionClassifierConfig = [argument.split(':') for argument in args.FU_cl_config]
-# fusionMethodConfig = [argument.split(':') for argument in args.FU_method_config]
-# FusionKWARGS = {"fusionType":args.FU_type, "fusionMethod":args.FU_method,
-# "monoviewClassifiersNames":fusionClassifierNames, "monoviewClassifiersConfigs":fusionClassifierConfig,
-# 'fusionMethodConfig':fusionMethodConfig}
-# MumboKWARGS = {"classifiersConfigs":mumboClassifierConfig, "NB_ITER":mumboNB_ITER, "classifiersNames":mumboclassifierNames}
-# directory = os.path.dirname(os.path.abspath(__file__)) + "/Results/"
-# logFileName = time.strftime("%Y%m%d-%H%M%S") + "-CMultiV-" + args.CL_type + "-" + "_".join(views) + "-" + args.name + \
-# "-LOG"
-# logFile = directory + logFileName
-# if os.path.isfile(logFile + ".log"):
-# for i in range(1, 20):
-# testFileName = logFileName + "-" + str(i) + ".log"
-# if not (os.path.isfile(directory + testFileName)):
-# logfile = directory + testFileName
-# break
-# else:
-# logFile += ".log"
-# logging.basicConfig(format='%(asctime)s %(levelname)s: %(message)s', filename=logFile, level=logging.DEBUG,
-# filemode='w')
-# if args.log:
-# logging.getLogger().addHandler(logging.StreamHandler())
-#
-# ExecMultiview(views, dataBaseType, args, NB_VIEW, LEARNING_RATE, nbFolds, NB_CLASS, LABELS_NAMES, NB_CORES,
-# MumboKWARGS, FusionKWARGS)
\ No newline at end of file
diff --git a/Code/FeatExtraction/DBCrawl.py b/Code/MonoMutliViewClassifiers/FeatExtraction/DBCrawl.py
similarity index 100%
rename from Code/FeatExtraction/DBCrawl.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/DBCrawl.py
diff --git a/Code/FeatExtraction/ExecFeatExtraction.py b/Code/MonoMutliViewClassifiers/FeatExtraction/ExecFeatExtraction.py
similarity index 100%
rename from Code/FeatExtraction/ExecFeatExtraction.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/ExecFeatExtraction.py
diff --git a/Code/FeatExtraction/ExecFeatParaOpt.py b/Code/MonoMutliViewClassifiers/FeatExtraction/ExecFeatParaOpt.py
similarity index 100%
rename from Code/FeatExtraction/ExecFeatParaOpt.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/ExecFeatParaOpt.py
diff --git a/Code/FeatExtraction/FeatExtraction.py b/Code/MonoMutliViewClassifiers/FeatExtraction/FeatExtraction.py
similarity index 100%
rename from Code/FeatExtraction/FeatExtraction.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/FeatExtraction.py
diff --git a/Code/FeatExtraction/FeatParaOpt.py b/Code/MonoMutliViewClassifiers/FeatExtraction/FeatParaOpt.py
similarity index 100%
rename from Code/FeatExtraction/FeatParaOpt.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/FeatParaOpt.py
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels-Description.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels-Description.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels-Description.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels-Description.csv
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-ClassLabels.csv
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HOG-CellDimension_5-nbOrientaions_8-nbClusters_20-Maxiter_100.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HOG-CellDimension_5-nbOrientaions_8-nbClusters_20-Maxiter_100.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HOG-CellDimension_5-nbOrientaions_8-nbClusters_20-Maxiter_100.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HOG-CellDimension_5-nbOrientaions_8-nbClusters_20-Maxiter_100.csv
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HSV-Bins_[16,16,16]-Norm_Distr.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HSV-Bins_[16,16,16]-Norm_Distr.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HSV-Bins_[16,16,16]-Norm_Distr.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-HSV-Bins_[16,16,16]-Norm_Distr.csv
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB-Bins_16-MaxCI_256-Norm_Distr.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB-Bins_16-MaxCI_256-Norm_Distr.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB-Bins_16-MaxCI_256-Norm_Distr.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB-Bins_16-MaxCI_256-Norm_Distr.csv
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB_HSV_SIFT_SURF_HOG-LOG.log b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB_HSV_SIFT_SURF_HOG-LOG.log
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB_HSV_SIFT_SURF_HOG-LOG.log
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-RGB_HSV_SIFT_SURF_HOG-LOG.log
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SIFT-Cluster_35-Norm_Distr.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SIFT-Cluster_35-Norm_Distr.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SIFT-Cluster_35-Norm_Distr.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SIFT-Cluster_35-Norm_Distr.csv
diff --git a/Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SURF-Cluster_30-Norm_Distr.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SURF-Cluster_30-Norm_Distr.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SURF-Cluster_30-Norm_Distr.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatExtr/2016_03_24-FE-Caltech-SURF-Cluster_30-Norm_Distr.csv
diff --git a/Code/FeatExtraction/Results-FeatParaOpt/HOG-10-50-5/2016_03_19-FeatParaOpt-HOG.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/HOG-10-50-5/2016_03_19-FeatParaOpt-HOG.csv
similarity index 100%
rename from Code/FeatExtraction/Results-FeatParaOpt/HOG-10-50-5/2016_03_19-FeatParaOpt-HOG.csv
rename to Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/HOG-10-50-5/2016_03_19-FeatParaOpt-HOG.csv
diff --git a/Code/FeatExtraction/Results-FeatParaOpt/HOG-10-50-5/2016_03_19-Feature_HOG-Parameter_HOG_Cluster-ClassTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/HOG-10-50-5/2016_03_19-Feature_HOG-Parameter_HOG_Cluster-ClassTime.png
similarity index 100%
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SIFT-2-40-8/2016_03_23-FPO-Caltech-SIFT-SIFT_Cluster-FeatExtTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SIFT-2-40-8/2016_03_23-FPO-Caltech-SIFT-SIFT_Cluster-FeatExtTime.png
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-2-25-5/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-ClassTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-2-25-5/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-ClassTime.png
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-2-25-5/2016_03_23-FPO-Caltech-SURF-SURF_Cluster.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-2-25-5/2016_03_23-FPO-Caltech-SURF-SURF_Cluster.csv
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-ClassTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-ClassTime.png
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-FeatExtTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-FeatExtTime.png
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-LOG-1.log b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-LOG-1.log
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-TotalTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-2-40-8/2016_03_23-FPO-Caltech-SURF-SURF_Cluster-TotalTime.png
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/2016_01_28-Results-SURF.csv b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/2016_01_28-Results-SURF.csv
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/Console-Output.txt b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/Console-Output.txt
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/ScoreClassificationTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/ScoreClassificationTime.png
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/ScoreFeatExtractionTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/ScoreFeatExtractionTime.png
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diff --git a/Code/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/ScoreTotalTime.png b/Code/MonoMutliViewClassifiers/FeatExtraction/Results-FeatParaOpt/SURF-50-200-4/ScoreTotalTime.png
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diff --git a/Code/FeatExtraction/__init__.py b/Code/MonoMutliViewClassifiers/FeatExtraction/__init__.py
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rename from Code/FeatExtraction/__init__.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/__init__.py
diff --git a/Code/FeatExtraction/hog_extraction.py b/Code/MonoMutliViewClassifiers/FeatExtraction/hog_extraction.py
similarity index 100%
rename from Code/FeatExtraction/hog_extraction.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/hog_extraction.py
diff --git a/Code/FeatExtraction/hog_extraction_parallelized.py b/Code/MonoMutliViewClassifiers/FeatExtraction/hog_extraction_parallelized.py
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rename from Code/FeatExtraction/hog_extraction_parallelized.py
rename to Code/MonoMutliViewClassifiers/FeatExtraction/hog_extraction_parallelized.py
diff --git a/Code/Monoview/ClassifMonoView.py b/Code/MonoMutliViewClassifiers/Monoview/ClassifMonoView.py
similarity index 90%
rename from Code/Monoview/ClassifMonoView.py
rename to Code/MonoMutliViewClassifiers/Monoview/ClassifMonoView.py
index d5b246b16a546f69a97b160f32d75edd38bba8cd..ebbad0fcd72787b41e9f3a9ea5638b50ecc6b832 100644
--- a/Code/Monoview/ClassifMonoView.py
+++ b/Code/MonoMutliViewClassifiers/Monoview/ClassifMonoView.py
@@ -168,16 +168,27 @@ def MonoviewClassifRandomForest(X_train, y_train, nbFolds=4, nbCores=1, **kwargs
return description, rf_detector
-def MonoviewClassifSVC(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
- pipeline_SVC = Pipeline([('classifier', sklearn.svm.SVC())])
- param_SVC = kwargs
+def MonoviewClassifSVMLinear(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_SVMLinear = Pipeline([('classifier', sklearn.svm.SVC())])
+ param_SVMLinear = kwargs
- grid_SVC = GridSearchCV(pipeline_SVC, param_grid=param_SVC, refit=True, n_jobs=nbCores, scoring='accuracy',
+ grid_SVMLinear = GridSearchCV(pipeline_SVMLinear, param_grid=param_SVMLinear, refit=True, n_jobs=nbCores, scoring='accuracy',
cv=nbFolds)
- SVC_detector = grid_SVC.fit(X_train, y_train)
- desc_params = [SVC_detector.best_params_["classifier__C"], SVC_detector.best_params_["classifier__kernel"]]
+ SVMLinear_detector = grid_SVMLinear.fit(X_train, y_train)
+ desc_params = [SVMLinear_detector.best_params_["classifier__C"]]
description = "Classif_" + "SVC" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
- return description, SVC_detector
+ return description, SVMLinear_detector
+
+def MonoviewClassifSVMRBF(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_SVMRBF = Pipeline([('classifier', sklearn.svm.SVC())])
+ param_SVMRBF = kwargs
+
+ grid_SVMRBF = GridSearchCV(pipeline_SVMRBF, param_grid=param_SVMRBF, refit=True, n_jobs=nbCores, scoring='accuracy',
+ cv=nbFolds)
+ SVMRBF_detector = grid_SVMRBF.fit(X_train, y_train)
+ desc_params = [SVMRBF_detector.best_params_["classifier__C"]]
+ description = "Classif_" + "SVC" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
+ return description, SVMRBF_detector
def MonoviewClassifDecisionTree(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
diff --git a/Code/Monoview/ExecClassifMonoView.py b/Code/MonoMutliViewClassifiers/Monoview/ExecClassifMonoView.py
similarity index 62%
rename from Code/Monoview/ExecClassifMonoView.py
rename to Code/MonoMutliViewClassifiers/Monoview/ExecClassifMonoView.py
index 04a271e7ea188ee11d08703307e8e5bc7a401f7c..55d4e86f2ecd52fb2e0e7d4e9ef304a09608d554 100644
--- a/Code/Monoview/ExecClassifMonoView.py
+++ b/Code/MonoMutliViewClassifiers/Monoview/ExecClassifMonoView.py
@@ -19,7 +19,7 @@ import h5py
# Import own modules
import ClassifMonoView # Functions for classification
import ExportResults # Functions to render results
-
+import MonoviewClassifiers
# Author-Info
__author__ = "Nikolas Huelsmann, Baptiste BAUVIN"
@@ -58,10 +58,10 @@ def ExecMonoview(X, Y, name, learningRate, nbFolds, nbCores, databaseType, path,
logging.debug("Start:\t Classification")
- classifierFunction = getattr(ClassifMonoView, "MonoviewClassif"+CL_type)
+ classifierModule = getattr(MonoviewClassifiers, CL_type)
+ classifierFunction = getattr(classifierModule, "fit_gridsearch")
- cl_desc, cl_res = classifierFunction(X_train, y_train, nbFolds=nbFolds, nbCores=nbCores,
- **classifierKWARGS)
+ cl_desc, cl_res = classifierFunction(X_train, y_train, nbFolds=nbFolds, nbCores=nbCores,**classifierKWARGS)
t_end = time.time() - t_start
# Add result to Results DF
@@ -91,37 +91,38 @@ def ExecMonoview(X, Y, name, learningRate, nbFolds, nbCores, databaseType, path,
#Accuracy classification score
accuracy_score = ExportResults.accuracy_score(y_test, y_test_pred)
-
- # Classification Report with Precision, Recall, F1 , Support
- logging.debug("Info:\t Classification report:")
- filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-Report"
- logging.debug("\n" + str(metrics.classification_report(y_test, y_test_pred, labels = range(0,len(classLabelsDesc.name)), target_names=classLabelsNamesList)))
- scores_df = ExportResults.classification_report_df(directory, filename, y_test, y_test_pred, range(0, len(classLabelsDesc.name)), classLabelsNamesList)
-
- # Create some useful statistcs
- logging.debug("Info:\t Statistics:")
- filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-Stats"
- stats_df = ExportResults.classification_stats(directory, filename, scores_df, accuracy_score)
- logging.debug("\n" + stats_df.to_string())
-
- # Confusion Matrix
- logging.debug("Info:\t Calculate Confusionmatrix")
- filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-ConfMatrix"
- df_conf_norm = ExportResults.confusion_matrix_df(directory, filename, y_test, y_test_pred, classLabelsNamesList)
- filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-ConfMatrixImg"
- ExportResults.plot_confusion_matrix(directory, filename, df_conf_norm)
-
- logging.debug("Done:\t Statistic Results")
-
-
- # Plot Result
- logging.debug("Start:\t Plot Result")
- np_score = ExportResults.calcScorePerClass(y_test, cl_res.predict(X_test).astype(int))
- ### directory and filename the same as CSV Export
- filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-Score"
- ExportResults.showResults(directory, filename, name, feat, np_score)
- logging.debug("Done:\t Plot Result")
- return [CL_type, accuracy_score, cl_desc]
+ logging.info("Accuracy :" +str(accuracy_score))
+
+ # # Classification Report with Precision, Recall, F1 , Support
+ # logging.debug("Info:\t Classification report:")
+ # filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-Report"
+ # logging.debug("\n" + str(metrics.classification_report(y_test, y_test_pred, labels = range(0,len(classLabelsDesc.name)), target_names=classLabelsNamesList)))
+ # scores_df = ExportResults.classification_report_df(directory, filename, y_test, y_test_pred, range(0, len(classLabelsDesc.name)), classLabelsNamesList)
+ #
+ # # Create some useful statistcs
+ # logging.debug("Info:\t Statistics:")
+ # filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-Stats"
+ # stats_df = ExportResults.classification_stats(directory, filename, scores_df, accuracy_score)
+ # logging.debug("\n" + stats_df.to_string())
+ #
+ # # Confusion Matrix
+ # logging.debug("Info:\t Calculate Confusionmatrix")
+ # filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-ConfMatrix"
+ # df_conf_norm = ExportResults.confusion_matrix_df(directory, filename, y_test, y_test_pred, classLabelsNamesList)
+ # filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-ConfMatrixImg"
+ # ExportResults.plot_confusion_matrix(directory, filename, df_conf_norm)
+ #
+ # logging.debug("Done:\t Statistic Results")
+ #
+ #
+ # # Plot Result
+ # logging.debug("Start:\t Plot Result")
+ # np_score = ExportResults.calcScorePerClass(y_test, cl_res.predict(X_test).astype(int))
+ # ### directory and filename the same as CSV Export
+ # filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + name + "-" + feat + "-Score"
+ # ExportResults.showResults(directory, filename, name, feat, np_score)
+ # logging.debug("Done:\t Plot Result")
+ # return [CL_type, accuracy_score, cl_desc]
if __name__=='__main__':
@@ -131,7 +132,7 @@ if __name__=='__main__':
groupStandard = parser.add_argument_group('Standard arguments')
groupStandard.add_argument('-log', action='store_true', help='Use option to activate Logging to Console')
- groupStandard.add_argument('--type', metavar='STRING', action='store', help='Type of Dataset', default="hdf5")
+ groupStandard.add_argument('--type', metavar='STRING', action='store', help='Type of Dataset', default=".hdf5")
groupStandard.add_argument('--name', metavar='STRING', action='store', help='Name of Database (default: %(default)s)', default='DB')
groupStandard.add_argument('--feat', metavar='STRING', action='store', help='Name of Feature for Classification (default: %(default)s)', default='RGB')
groupStandard.add_argument('--pathF', metavar='STRING', action='store', help='Path to the views (default: %(default)s)', default='Results-FeatExtr/')
@@ -147,34 +148,39 @@ if __name__=='__main__':
groupClass.add_argument('--CL_split', metavar='FLOAT', action='store', help='Split ratio for train and test', type=float, default=0.9)
- groupRF = parser.add_argument_group('Random Forest arguments')
- groupRF.add_argument('--CL_RF_trees', metavar='STRING', action='store', help='GridSearch: Determine the trees', default='25 75 125 175')
-
- groupSVC = parser.add_argument_group('SVC arguments')
- groupSVC.add_argument('--CL_SVC_kernel', metavar='STRING', action='store', help='GridSearch : Kernels used', default='linear')
- groupSVC.add_argument('--CL_SVC_C', metavar='STRING', action='store', help='GridSearch : Penalty parameters used', default='1:10:100:1000')
+ groupClassifier = parser.add_argument_group('Classifier Config')
+ groupClassifier.add_argument('--CL_config', metavar='STRING', nargs="+", action='store', help='GridSearch: Determine the trees', default=['25:75:125:175'])
- groupRF = parser.add_argument_group('Decision Trees arguments')
- groupRF.add_argument('--CL_DT_depth', metavar='STRING', action='store', help='GridSearch: Determine max depth for Decision Trees', default='1:3:5:7')
-
- groupSGD = parser.add_argument_group('SGD arguments')
- groupSGD.add_argument('--CL_SGD_alpha', metavar='STRING', action='store', help='GridSearch: Determine alpha for SGDClassifier', default='0.1:0.2:0.5:0.9')
- groupSGD.add_argument('--CL_SGD_loss', metavar='STRING', action='store', help='GridSearch: Determine loss for SGDClassifier', default='log')
- groupSGD.add_argument('--CL_SGD_penalty', metavar='STRING', action='store', help='GridSearch: Determine penalty for SGDClassifier', default='l2')
+ # groupSVMLinear = parser.add_argument_group('SVC arguments')
+ # groupSVMLinear.add_argument('--CL_SVML_C', metavar='STRING', action='store', help='GridSearch : Penalty parameters used', default='1:10:100:1000')
+ #
+ # groupSVMRBF = parser.add_argument_group('SVC arguments')
+ # groupSVMRBF.add_argument('--CL_SVMR_C', metavar='STRING', action='store', help='GridSearch : Penalty parameters used', default='1:10:100:1000')
+ #
+ # groupRF = parser.add_argument_group('Decision Trees arguments')
+ # groupRF.add_argument('--CL_DT_depth', metavar='STRING', action='store', help='GridSearch: Determine max depth for Decision Trees', default='1:3:5:7')
+ #
+ # groupSGD = parser.add_argument_group('SGD')
+ # groupSGD.add_argument('--CL_SGD_alpha', metavar='STRING', action='store', help='GridSearch: Determine alpha for SGDClassifier', default='0.1:0.2:0.5:0.9')
+ # groupSGD.add_argument('--CL_SGD_loss', metavar='STRING', action='store', help='GridSearch: Determine loss for SGDClassifier', default='log')
+ # groupSGD.add_argument('--CL_SGD_penalty', metavar='STRING', action='store', help='GridSearch: Determine penalty for SGDClassifier', default='l2')
args = parser.parse_args()
- RandomForestKWARGS = {"classifier__n_estimators":map(int, args.CL_RF_trees.split())}
- SVCKWARGS = {"classifier__kernel":args.CL_SVC_kernel.split(":"), "classifier__C":map(int,args.CL_SVC_C.split(":"))}
- DecisionTreeKWARGS = {"classifier__max_depth":map(int,args.CL_DT_depth.split(":"))}
- SGDKWARGS = {"classifier__alpha" : map(float,args.CL_SGD_alpha.split(":")), "classifier__loss":args.CL_SGD_loss.split(":"),
- "classifier__penalty":args.CL_SGD_penalty.split(":")}
+
+ # RandomForestKWARGS = {"classifier__n_estimators":map(int, args.CL_RF_trees.split())}
+ # SVMLinearKWARGS = {"classifier__C":map(int,args.CL_SVML_C.split(":"))}
+ # SVMRBFKWARGS = {"classifier__C":map(int,args.CL_SVMR_C.split(":"))}
+ # DecisionTreeKWARGS = {"classifier__max_depth":map(int,args.CL_DT_depth.split(":"))}
+ # SGDKWARGS = {"classifier__alpha" : map(float,args.CL_SGD_alpha.split(":")), "classifier__loss":args.CL_SGD_loss.split(":"),
+ # "classifier__penalty":args.CL_SGD_penalty.split(":")}
+ classifierKWARGS = dict((key, value) for key, value in enumerate([arg.split(":") for arg in args.CL_config]))
### Main Programm
# Configure Logger
directory = os.path.dirname(os.path.abspath(__file__)) + "/Results-ClassMonoView/"
- logfilename= datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + args.name + "-" + args.feat + "-LOG"
+ logfilename = datetime.datetime.now().strftime("%Y_%m_%d") + "-CMV-" + args.name + "-" + args.feat + "-LOG"
logfile = directory + logfilename
if os.path.isfile(logfile + ".log"):
for i in range(1,20):
@@ -194,7 +200,7 @@ if __name__=='__main__':
# Read the features
logging.debug("Start:\t Read " + args.type + " Files")
- if args.databaseType == ".csv":
+ if args.type == ".csv":
X = np.genfromtxt(args.pathF + args.fileFeat, delimiter=';')
Y = np.genfromtxt(args.pathF + args.fileCL, delimiter=';')
elif args.type == ".hdf5":
@@ -206,7 +212,6 @@ if __name__=='__main__':
logging.debug("Info:\t Shape of Feature:" + str(X.shape) + ", Length of classLabels vector:" + str(Y.shape))
logging.debug("Done:\t Read CSV Files")
- arguments = {"RandomForestKWARGS": RandomForestKWARGS, "SVCKWARGS": SVCKWARGS,
- "DecisionTreeKWARGS": DecisionTreeKWARGS, "SGDKWARGS": SGDKWARGS, "feat":args.feat,
- "fileFeat": args.fileFeat, "fileCL": args.fileCL, "fileCLD": args.fileCLD, "CL_type": args.CL_type}
+ arguments = {args.CL_type+"KWARGS": classifierKWARGS, "feat":args.feat,"fileFeat": args.fileFeat,
+ "fileCL": args.fileCL, "fileCLD": args.fileCLD, "CL_type": args.CL_type}
ExecMonoview(X, Y, args.name, args.CL_split, args.CL_CV, args.CL_Cores, args.type, args.pathF, **arguments)
diff --git a/Code/Monoview/ExecPlot.py b/Code/MonoMutliViewClassifiers/Monoview/ExecPlot.py
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-1.log b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-1.log
new file mode 100644
index 0000000000000000000000000000000000000000..e0257febb4eea9d80de959b9f56d9ee37e3b0283
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-1.log
@@ -0,0 +1 @@
+2016-08-24 15:07:02,885 DEBUG: Start: Read hdf5 Files
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-2.log b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-2.log
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index 0000000000000000000000000000000000000000..16ce3c6ff27d49df2f13392ff31334c8f8be78de
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-2.log
@@ -0,0 +1 @@
+2016-08-24 15:07:32,272 DEBUG: Start: Read hdf5 Files
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-3.log b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-3.log
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index 0000000000000000000000000000000000000000..3f44f8ec4d6215d6cc98cdc63d2014c797b071ae
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG-3.log
@@ -0,0 +1 @@
+2016-08-24 15:07:49,531 DEBUG: Start: Read .hdf5 Files
diff --git a/Code/Multiview/Results/20160819-202408-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-MultiOmicModified-LOG.log b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-DB-RGB-LOG.log
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rename from Code/Multiview/Results/20160819-202408-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-MultiOmicModified-LOG.log
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-ConfMatrix-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-ConfMatrix-1.csv
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index 0000000000000000000000000000000000000000..b49e4ceecad081b72c1104cdd30b0860a83f580f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-ConfMatrix-1.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.480769230769;0.0555555555556;0.371428571429
+Oui;0.173076923077;0.0;0.128571428571
+All;0.653846153846;0.0555555555556;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-ConfMatrix-2.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-ConfMatrix-2.csv
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Score.png b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Score.png
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ed7e4d7689e5cdf56f0ccc7d1f8bb5718f236e5b
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-1.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.41666666666666663
+5;Mean of F1-Score of top 20 classes by F1-Score;0.41666666666666663
+6;Mean of F1-Score of top 30 classes by F1-Score;0.41666666666666663
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-2.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1c2dbd1ed3d5e7aa0ba1c89d2ba57f3e19bfd640
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-2.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.514285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.42176870748299317
+5;Mean of F1-Score of top 20 classes by F1-Score;0.42176870748299317
+6;Mean of F1-Score of top 30 classes by F1-Score;0.42176870748299317
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-3.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-3.csv
new file mode 100644
index 0000000000000000000000000000000000000000..43b035de3d0a086c09a1629d5ac058af32eb9da5
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-3.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.628571428571
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.4950055493895672
+5;Mean of F1-Score of top 20 classes by F1-Score;0.4950055493895672
+6;Mean of F1-Score of top 30 classes by F1-Score;0.4950055493895672
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-4.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-4.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ed7e4d7689e5cdf56f0ccc7d1f8bb5718f236e5b
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-4.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.41666666666666663
+5;Mean of F1-Score of top 20 classes by F1-Score;0.41666666666666663
+6;Mean of F1-Score of top 30 classes by F1-Score;0.41666666666666663
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-5.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-5.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bf6df6d6a7cb9b98a969c35f65c070ccd3412063
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-5.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.49712643678160917
+5;Mean of F1-Score of top 20 classes by F1-Score;0.49712643678160917
+6;Mean of F1-Score of top 30 classes by F1-Score;0.49712643678160917
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-6.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-6.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d62c8a0ec75abd7daf79968d389a15a0e536dd06
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-6.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.571428571429
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.4582043343653251
+5;Mean of F1-Score of top 20 classes by F1-Score;0.4582043343653251
+6;Mean of F1-Score of top 30 classes by F1-Score;0.4582043343653251
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-7.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-7.csv
new file mode 100644
index 0000000000000000000000000000000000000000..81997a605bbe046bca245ba499134b1116344c3b
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-7.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.6
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.5359848484848485
+5;Mean of F1-Score of top 20 classes by F1-Score;0.5359848484848485
+6;Mean of F1-Score of top 30 classes by F1-Score;0.5359848484848485
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-8.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-8.csv
new file mode 100644
index 0000000000000000000000000000000000000000..afae0799dcfdb3579306c4fc670f38b76ec3d91b
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-8.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.742857142857
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.6181818181818182
+5;Mean of F1-Score of top 20 classes by F1-Score;0.6181818181818182
+6;Mean of F1-Score of top 30 classes by F1-Score;0.6181818181818182
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-9.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-9.csv
new file mode 100644
index 0000000000000000000000000000000000000000..69922632bbd248d18b1b00a3ab99d7757879e62a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats-9.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.771428571429
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.435483870967742
+5;Mean of F1-Score of top 20 classes by F1-Score;0.435483870967742
+6;Mean of F1-Score of top 30 classes by F1-Score;0.435483870967742
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cfd6be913a6c4de93236cf47f6d3a2b531615b5a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Clinic-Stats.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.657142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.39655172413793105
+5;Mean of F1-Score of top 20 classes by F1-Score;0.39655172413793105
+6;Mean of F1-Score of top 30 classes by F1-Score;0.39655172413793105
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..695d8c1ea27038b160edd191d34248fee6914547
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-1.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.5;;0.357142857143
+Oui;0.2;;0.142857142857
+All;0.7;;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-2.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c37d7e485cc7ddf323cd5b821ca5723a81483d1a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-2.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.5;;0.342857142857
+Oui;0.229166666667;;0.157142857143
+All;0.729166666667;;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-3.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-3.csv
new file mode 100644
index 0000000000000000000000000000000000000000..304fcfb669d7f78240f8a8c0d6fe583fd6fa1fb3
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-3.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.5;0.0;0.4
+Oui;0.0714285714286;0.214285714286;0.1
+All;0.571428571429;0.214285714286;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-4.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-4.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ef2cbd67e6a98cce4e354b9bf69666eb440126b8
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-4.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.0714285714286;1.71428571429;0.4
+Oui;0.0;0.5;0.1
+All;0.0714285714286;2.21428571429;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-5.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-5.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8a9c04e6f30d41ca6d393c29f0a6cf6cbd5c4725
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-5.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.433333333333;0.4;0.428571428571
+Oui;0.0333333333333;0.3;0.0714285714286
+All;0.466666666667;0.7;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-6.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-6.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d7ed7a70e08e5256bfe653c244aade9ec2fc0985
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-6.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.407407407407;0.3125;0.385714285714
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+All;0.5;0.5;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-7.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-7.csv
new file mode 100644
index 0000000000000000000000000000000000000000..51fe732559e04a6e8b994257a29ccb58ddf7d953
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix-7.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.5;;0.328571428571
+Oui;0.260869565217;;0.171428571429
+All;0.760869565217;;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix.csv
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index 0000000000000000000000000000000000000000..08010776bdba6fb15a25cfbe6c67aa0d9f544994
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrix.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.5;0.0;0.3
+Oui;0.047619047619;0.428571428571;0.2
+All;0.547619047619;0.428571428571;0.5
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrixImg.png b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-ConfMatrixImg.png
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e4303ee3cde40960f928ba80668fd30ed42da210
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-1.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.714285714286;1.0;0.833333333333;25.0
+Oui;0.0;0.0;0.0;10.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-2.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..45417716354c392e85f7f1960ac02a701a0b7df6
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-2.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.685714285714;1.0;0.813559322034;24.0
+Oui;0.0;0.0;0.0;11.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-3.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-3.csv
new file mode 100644
index 0000000000000000000000000000000000000000..17ba1f5a9e4eb020d79ff2b3582b49b426c3f7ab
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-3.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.875;1.0;0.933333333333;28.0
+Oui;1.0;0.428571428571;0.6;7.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-4.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-4.csv
new file mode 100644
index 0000000000000000000000000000000000000000..28ebc0f98c943519125e52c31dc0c19290790694
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-4.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;1.0;0.142857142857;0.25;28.0
+Oui;0.225806451613;1.0;0.368421052632;7.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-5.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-5.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e9f4be6ff854a6f29bfd88672a9a2c936cfea95e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-5.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.928571428571;0.866666666667;0.896551724138;30.0
+Oui;0.428571428571;0.6;0.5;5.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-6.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-6.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2b667c599d73da80fad654c55bdb117c450a0769
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-6.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.814814814815;0.814814814815;0.814814814815;27.0
+Oui;0.375;0.375;0.375;8.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-7.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-7.csv
new file mode 100644
index 0000000000000000000000000000000000000000..65942d65303e134789f2ef5e59e68acbbbb20e89
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report-7.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.657142857143;1.0;0.793103448276;23.0
+Oui;0.0;0.0;0.0;12.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report.csv
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index 0000000000000000000000000000000000000000..ced61b510ad73b9d2effe5d8d8c20c33fb4361f3
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Report.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.913043478261;1.0;0.954545454545;21.0
+Oui;1.0;0.857142857143;0.923076923077;14.0
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ed7e4d7689e5cdf56f0ccc7d1f8bb5718f236e5b
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-1.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.41666666666666663
+5;Mean of F1-Score of top 20 classes by F1-Score;0.41666666666666663
+6;Mean of F1-Score of top 30 classes by F1-Score;0.41666666666666663
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-2.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fb3b57b1ad14692b305fb2473f3d50e46bee21e3
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-2.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.685714285714
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.4067796610169492
+5;Mean of F1-Score of top 20 classes by F1-Score;0.4067796610169492
+6;Mean of F1-Score of top 30 classes by F1-Score;0.4067796610169492
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-3.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-3.csv
new file mode 100644
index 0000000000000000000000000000000000000000..12e7af6ddbed4b11d59b32f43d3a4c8865b4ff2f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-3.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.885714285714
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7666666666666666
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7666666666666666
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7666666666666666
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-4.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-4.csv
new file mode 100644
index 0000000000000000000000000000000000000000..27f52192acc9aa81a5cec395d640060199f8f626
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-4.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.314285714286
+1;Top 10 classes by F1-Score;['Oui', 'Non']
+2;Worst 10 classes by F1-Score;['Non', 'Oui']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.3092105263157895
+5;Mean of F1-Score of top 20 classes by F1-Score;0.3092105263157895
+6;Mean of F1-Score of top 30 classes by F1-Score;0.3092105263157895
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-5.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-5.csv
new file mode 100644
index 0000000000000000000000000000000000000000..410f8862a8cedf20702b4af831b1fdb58cde37a1
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-5.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.828571428571
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.6982758620689655
+5;Mean of F1-Score of top 20 classes by F1-Score;0.6982758620689655
+6;Mean of F1-Score of top 30 classes by F1-Score;0.6982758620689655
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-6.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-6.csv
new file mode 100644
index 0000000000000000000000000000000000000000..af2aaa26e7d17e7acda19b322818cacd99eccc7e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-6.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.5949074074074074
+5;Mean of F1-Score of top 20 classes by F1-Score;0.5949074074074074
+6;Mean of F1-Score of top 30 classes by F1-Score;0.5949074074074074
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-7.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-7.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cfd6be913a6c4de93236cf47f6d3a2b531615b5a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats-7.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.657142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.39655172413793105
+5;Mean of F1-Score of top 20 classes by F1-Score;0.39655172413793105
+6;Mean of F1-Score of top 30 classes by F1-Score;0.39655172413793105
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats.csv
new file mode 100644
index 0000000000000000000000000000000000000000..272496167e1e24075fa66e2099291317698900cc
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-Methyl-Stats.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.942857142857
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.9388111888111887
+5;Mean of F1-Score of top 20 classes by F1-Score;0.9388111888111887
+6;Mean of F1-Score of top 30 classes by F1-Score;0.9388111888111887
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a13e82013d4bc4028b34eaf4c851cbab423d25af
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-1.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.458333333333;0.0909090909091;0.342857142857
+Oui;0.0625;0.363636363636;0.157142857143
+All;0.520833333333;0.454545454545;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-10.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-10.csv
new file mode 100644
index 0000000000000000000000000000000000000000..23380cfc5073633692eb40f48025b685ae064317
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-10.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.431034482759;0.333333333333;0.414285714286
+Oui;0.0172413793103;0.416666666667;0.0857142857143
+All;0.448275862069;0.75;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-11.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-11.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ec20de4efaf3f600e1cc1b3865c0fb858033fb75
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-11.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.451612903226;0.375;0.442857142857
+Oui;0.0161290322581;0.375;0.0571428571429
+All;0.467741935484;0.75;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-12.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-12.csv
new file mode 100644
index 0000000000000000000000000000000000000000..0d9e7845f15bf58b2de9d7e8a6d8a1e16d65f10a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-12.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.454545454545;0.0769230769231;0.314285714286
+Oui;0.0681818181818;0.384615384615;0.185714285714
+All;0.522727272727;0.461538461538;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-13.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-13.csv
new file mode 100644
index 0000000000000000000000000000000000000000..29d473564b4ef2a4ef2ee25e78b7e03147c6c8d3
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-13.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.466666666667;0.2;0.428571428571
+Oui;0.0166666666667;0.4;0.0714285714286
+All;0.483333333333;0.6;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-14.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-14.csv
new file mode 100644
index 0000000000000000000000000000000000000000..edbbae5e38e30da3a62c280d7d534d476bf4ea83
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-14.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.410714285714;0.357142857143;0.4
+Oui;0.0;0.5;0.1
+All;0.410714285714;0.857142857143;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-15.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-ConfMatrix-15.csv
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..81f0fd88b0e07eb1521dd38aaaed284428b69154
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-1.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.857142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8299319727891157
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8299319727891157
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8299319727891157
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-10.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-10.csv
new file mode 100644
index 0000000000000000000000000000000000000000..133d2853fe84235749540a3b5fd5fe79544ca6e3
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-10.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.857142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7878787878787878
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7878787878787878
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7878787878787878
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-11.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-11.csv
new file mode 100644
index 0000000000000000000000000000000000000000..12e7af6ddbed4b11d59b32f43d3a4c8865b4ff2f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-11.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.885714285714
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7666666666666666
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7666666666666666
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7666666666666666
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-12.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-12.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bf63027079c9e6ed9c224c804ba841815a777019
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-12.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.857142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8444444444444446
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8444444444444446
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8444444444444446
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-13.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-13.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b08246526eae3ac7b06dd90c9959eb8ceed4b2bd
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-13.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.914285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8382126348228043
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8382126348228043
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8382126348228043
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-14.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-14.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9f142c0de6e22e6cd7864cd8143892a566415238
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-14.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.857142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8194014447884417
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8194014447884417
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8194014447884417
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-15.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-15.csv
new file mode 100644
index 0000000000000000000000000000000000000000..441e24d82bfd8fcbd7603222f4afffc074aae6a8
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-15.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.828571428571
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7569444444444445
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7569444444444445
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7569444444444445
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-16.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-16.csv
new file mode 100644
index 0000000000000000000000000000000000000000..43c2dad0215d3aec1a753dace55ad721099a81f1
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-16.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7733580018501388
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7733580018501388
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7733580018501388
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-17.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-17.csv
new file mode 100644
index 0000000000000000000000000000000000000000..211b411f9024e8944367f307ebfda63dffe72e87
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-17.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.742857142857
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.72
+5;Mean of F1-Score of top 20 classes by F1-Score;0.72
+6;Mean of F1-Score of top 30 classes by F1-Score;0.72
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-18.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-18.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11c46e226a09844b0539edbac395bc8a69bb7678
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-18.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.828571428571
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7569444444444444
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7569444444444444
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7569444444444444
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-19.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-19.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9f142c0de6e22e6cd7864cd8143892a566415238
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-19.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.857142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8194014447884417
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8194014447884417
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8194014447884417
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-2.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5dbd75e8eeae421b1288f1f9c9488f5bb6b7a8e7
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-2.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.828571428571
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8011363636363638
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8011363636363638
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8011363636363638
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-3.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-3.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4d47e5bf6e3be8f048844078df8e7edbae440e6c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-3.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7619047619047619
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7619047619047619
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7619047619047619
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-4.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-4.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c557de1fde12557b9cee63b431a8e200e4b91c6d
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-4.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.885714285714
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8776223776223775
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8776223776223775
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8776223776223775
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-5.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-5.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2e90b7ca5db6776b5d1027cc769b3d2dbac165d4
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-5.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.942857142857
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8994252873563219
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8994252873563219
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8994252873563219
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-6.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-6.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9ac22152452ec94987ca805187a4c2f8f862781e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-6.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.914285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8916408668730651
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8916408668730651
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8916408668730651
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-7.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-7.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bb35623c7590a57be471437e7943a59d5e280cd3
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-7.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.771428571429
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7008547008547008
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7008547008547008
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7008547008547008
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-8.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-8.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2711eacadd16eb1e304d7fc3daf26ef296a3e358
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-8.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7822222222222223
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7822222222222223
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7822222222222223
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-9.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-9.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3cfd0b1093e29b9e5ed35159ff005fc201b27b54
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats-9.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.942857142857
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8994252873563218
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8994252873563218
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8994252873563218
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bf63027079c9e6ed9c224c804ba841815a777019
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-MiRNA_-Stats.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.857142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8444444444444446
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8444444444444446
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8444444444444446
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-ConfMatrix-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-ConfMatrix-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..3ab1dc38f544b13d936afd8fe27f546a7033fe19
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-ConfMatrix-1.csv
@@ -0,0 +1,4 @@
+;Non;Oui;All
+Non;0.481481481481;0.0625;0.385714285714
+Oui;0.0185185185185;0.4375;0.114285714286
+All;0.5;0.5;0.5
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-ConfMatrix-10.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-ConfMatrix-10.csv
new file mode 100644
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+Oui;0.272727272727;0.6;0.375;5.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-5.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-5.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e4303ee3cde40960f928ba80668fd30ed42da210
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-5.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.714285714286;1.0;0.833333333333;25.0
+Oui;0.0;0.0;0.0;10.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-6.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-6.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8f3d332ebe9f5b64c51f9e94a0fb53d9167c71c4
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-6.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.84;0.875;0.857142857143;24.0
+Oui;0.7;0.636363636364;0.666666666667;11.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-7.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-7.csv
new file mode 100644
index 0000000000000000000000000000000000000000..9f28f5f8f35b3f9d90dace8edb271de4da6d4871
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-7.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.851851851852;0.92;0.884615384615;25.0
+Oui;0.75;0.6;0.666666666667;10.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-8.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-8.csv
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index 0000000000000000000000000000000000000000..a7efd348cdedf1d979077992e25a89543fc4c0f2
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-8.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.833333333333;0.925925925926;0.877192982456;27.0
+Oui;0.6;0.375;0.461538461538;8.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-9.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-9.csv
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index 0000000000000000000000000000000000000000..24ffa0fc33d7218b929d84d5e09c3443ab6c0c99
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+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report-9.csv
@@ -0,0 +1,3 @@
+;Precision;Recall;F1;Support
+Non;0.925925925926;0.961538461538;0.943396226415;26.0
+Oui;0.875;0.777777777778;0.823529411765;9.0
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report.csv
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index 0000000000000000000000000000000000000000..d74decdbb6765f562440122a9a24892c69cfbcbf
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+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Report.csv
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+;Precision;Recall;F1;Support
+Non;0.814814814815;0.916666666667;0.862745098039;24.0
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diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-1.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-1.csv
new file mode 100644
index 0000000000000000000000000000000000000000..8ac6cb3bdebd6c7ac8697bd10799ee2a54cd21b3
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-1.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.942857142857
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.9189814814814814
+5;Mean of F1-Score of top 20 classes by F1-Score;0.9189814814814814
+6;Mean of F1-Score of top 30 classes by F1-Score;0.9189814814814814
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-10.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-10.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a3cebc6081af51288a719fb22e2559fc25e901fe
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-10.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.742857142857
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7086031452358927
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7086031452358927
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7086031452358927
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-11.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-11.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cd13999012acd2ec54283845347f06e74ab1a735
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-11.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.857142857143
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8492678725236864
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8492678725236864
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8492678725236864
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-12.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-12.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cadf36d58e74289ab5f1487f493680ed50dda497
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-12.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.703030303030303
+5;Mean of F1-Score of top 20 classes by F1-Score;0.703030303030303
+6;Mean of F1-Score of top 30 classes by F1-Score;0.703030303030303
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-13.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-13.csv
new file mode 100644
index 0000000000000000000000000000000000000000..32d51bf0a55837676b1e74f5f640d863e1b08895
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-13.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.4444444444444445
+5;Mean of F1-Score of top 20 classes by F1-Score;0.4444444444444445
+6;Mean of F1-Score of top 30 classes by F1-Score;0.4444444444444445
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-2.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-2.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b08246526eae3ac7b06dd90c9959eb8ceed4b2bd
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-2.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.914285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8382126348228043
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8382126348228043
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8382126348228043
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-3.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-3.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6084f669bac7ad1259e74ef61a4cf8593ea8cb3c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-3.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7083333333333333
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7083333333333333
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7083333333333333
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-4.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-4.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e0b61f246c06bd747366654c1261701d562f5484
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-4.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.5949074074074073
+5;Mean of F1-Score of top 20 classes by F1-Score;0.5949074074074073
+6;Mean of F1-Score of top 30 classes by F1-Score;0.5949074074074073
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-5.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-5.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ed7e4d7689e5cdf56f0ccc7d1f8bb5718f236e5b
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-5.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.714285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.5
+4;Mean of F1-Score of top 10 classes by F1-Score;0.41666666666666663
+5;Mean of F1-Score of top 20 classes by F1-Score;0.41666666666666663
+6;Mean of F1-Score of top 30 classes by F1-Score;0.41666666666666663
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-6.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-6.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4d47e5bf6e3be8f048844078df8e7edbae440e6c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-6.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7619047619047619
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7619047619047619
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7619047619047619
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-7.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-7.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e0555824ca01d3107bb9fe860c222a925c504c54
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-7.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.828571428571
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7756410256410255
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7756410256410255
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7756410256410255
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-8.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-8.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b5d750fca3497c96dadd4f4e68f72cb00cc1abe7
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-8.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.6693657219973009
+5;Mean of F1-Score of top 20 classes by F1-Score;0.6693657219973009
+6;Mean of F1-Score of top 30 classes by F1-Score;0.6693657219973009
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-9.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-9.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b80ac1fdbface94e7feb55290ab3eda20a70a7be
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats-9.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.914285714286
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.8834628190899001
+5;Mean of F1-Score of top 20 classes by F1-Score;0.8834628190899001
+6;Mean of F1-Score of top 30 classes by F1-Score;0.8834628190899001
diff --git a/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats.csv
new file mode 100644
index 0000000000000000000000000000000000000000..aaf58c084a76e2e4543327f1f0c84a39e253a6d6
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/2016_08_24-CMV-MultiOmic-RNASeq-Stats.csv
@@ -0,0 +1,8 @@
+;Statistic;Values
+0;Accuracy score on test;0.8
+1;Top 10 classes by F1-Score;['Non', 'Oui']
+2;Worst 10 classes by F1-Score;['Oui', 'Non']
+3;Ratio of classes with F1-Score==0 of all classes;0.0
+4;Mean of F1-Score of top 10 classes by F1-Score;0.7471620227038183
+5;Mean of F1-Score of top 20 classes by F1-Score;0.7471620227038183
+6;Mean of F1-Score of top 30 classes by F1-Score;0.7471620227038183
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diff --git a/Code/Monoview/Results-ClassMonoView/SIFT-Cluster_35/2016_03_24-CMV-Caltech-SIFT.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SIFT-Cluster_35/2016_03_24-CMV-Caltech-SIFT.csv
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rename from Code/Monoview/Results-ClassMonoView/SIFT-Cluster_35/2016_03_24-CMV-Caltech-SIFT.csv
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SIFT-Cluster_35/2016_03_24-CMV-Caltech-SIFT.csv
diff --git a/Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrix.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrix.csv
similarity index 100%
rename from Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrix.csv
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrix.csv
diff --git a/Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrixImg.png b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrixImg.png
similarity index 100%
rename from Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrixImg.png
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-ConfMatrixImg.png
diff --git a/Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-LOG.log b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-LOG.log
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rename from Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-LOG.log
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-LOG.log
diff --git a/Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Report.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Report.csv
similarity index 100%
rename from Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Report.csv
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Report.csv
diff --git a/Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Score.png b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Score.png
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rename from Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Score.png
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Score.png
diff --git a/Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Stats.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Stats.csv
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rename from Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Stats.csv
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF-Stats.csv
diff --git a/Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF.csv b/Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF.csv
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rename from Code/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF.csv
rename to Code/MonoMutliViewClassifiers/Monoview/Results-ClassMonoView/SURF-Cluster_30/2016_03_24-CMV-Caltech-SURF.csv
diff --git a/Code/Monoview/__init__.py b/Code/MonoMutliViewClassifiers/Monoview/__init__.py
similarity index 100%
rename from Code/Monoview/__init__.py
rename to Code/MonoMutliViewClassifiers/Monoview/__init__.py
diff --git a/Code/Monoview/run.py b/Code/MonoMutliViewClassifiers/Monoview/run.py
similarity index 100%
rename from Code/Monoview/run.py
rename to Code/MonoMutliViewClassifiers/Monoview/run.py
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/Adaboost.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/Adaboost.py
new file mode 100644
index 0000000000000000000000000000000000000000..d1c45281a2105e7c5b16d1d8d91cda5d84c000a8
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/Adaboost.py
@@ -0,0 +1,28 @@
+from sklearn.ensemble import AdaBoostClassifier
+from sklearn.pipeline import Pipeline
+from sklearn.grid_search import GridSearchCV
+from sklearn.tree import DecisionTreeClassifier
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
+ num_estimators = int(kwargs['0'])
+ base_estimators = int(kwargs['1'])
+ classifier = AdaBoostClassifier(n_estimators=num_estimators, base_estimator=base_estimators)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+
+ pipeline = Pipeline([('classifier', AdaBoostClassifier())])
+ param= {"classifier__n_estimators": map(int, kwargs['0']),
+ "classifier__base_estimator": [DecisionTreeClassifier() for arg in kwargs["1"]]}
+ grid = GridSearchCV(pipeline,param_grid=param,refit=True,n_jobs=nbCores,scoring='accuracy',cv=nbFolds)
+ detector = grid.fit(X_train, y_train)
+ desc_estimators = [detector.best_params_["classifier__n_estimators"]]
+ description = "Classif_" + "RF" + "-" + "CV_" + str(nbFolds) + "-" + "Trees_" + str(map(str,desc_estimators))
+ return description, detector
+
+
+def getConfig(config):
+ return "\n\t\t- Adaboost with num_esimators : "+config[0]+", base_estimators : "+config[1]
\ No newline at end of file
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/DecisionTree.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/DecisionTree.py
new file mode 100644
index 0000000000000000000000000000000000000000..8fe4de8daf27ffa9bcf7e4f4c33fd5d665ee03b7
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/DecisionTree.py
@@ -0,0 +1,26 @@
+from sklearn.tree import DecisionTreeClassifier
+from sklearn.pipeline import Pipeline # Pipelining in classification
+from sklearn.grid_search import GridSearchCV
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1, **kwargs):
+ maxDepth = int(kwargs['0'])
+ classifier = DecisionTreeClassifier(max_depth=maxDepth)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_DT = Pipeline([('classifier', DecisionTreeClassifier())])
+ param_DT = {"classifier__max_depth":map(int, kwargs['0'])}
+
+ grid_DT = GridSearchCV(pipeline_DT, param_grid=param_DT, refit=True, n_jobs=nbCores, scoring='accuracy',
+ cv=nbFolds)
+ DT_detector = grid_DT.fit(X_train, y_train)
+ desc_params = [DT_detector.best_params_["classifier__max_depth"]]
+ description = "Classif_" + "DT" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
+ return description, DT_detector
+
+
+def getConfig(config):
+ return "\n\t\t- Decision Tree with max_depth : "+config[0]
\ No newline at end of file
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/KNN.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/KNN.py
new file mode 100644
index 0000000000000000000000000000000000000000..ae03c3555610b793ef54c94baa157ba3df1df32e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/KNN.py
@@ -0,0 +1,26 @@
+from sklearn.neighbors import KNeighborsClassifier
+from sklearn.pipeline import Pipeline # Pipelining in classification
+from sklearn.grid_search import GridSearchCV
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
+ nNeighbors = int(kwargs['0'])
+ classifier = KNeighborsClassifier(n_neighbors=nNeighbors)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_KNN = Pipeline([('classifier', KNeighborsClassifier())])
+ param_KNN = {"classifier__n_neighbors": map(int, kwargs['0'])}
+ grid_KNN = GridSearchCV(pipeline_KNN, param_grid=param_KNN, refit=True, n_jobs=nbCores, scoring='accuracy',
+ cv=nbFolds)
+ KNN_detector = grid_KNN.fit(X_train, y_train)
+ desc_params = [KNN_detector.best_params_["classifier__n_neighbors"]]
+ description = "Classif_" + "Lasso" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
+ return description, KNN_detector
+
+
+
+def getConfig(config):
+ return "\n\t\t- K nearest Neighbors with n_neighbors: "+config[0]
\ No newline at end of file
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/RandomForest.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/RandomForest.py
new file mode 100644
index 0000000000000000000000000000000000000000..968d83d2f66abec190c9dcf0510b36e148d1cd0e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/RandomForest.py
@@ -0,0 +1,46 @@
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.pipeline import Pipeline
+from sklearn.grid_search import GridSearchCV
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
+ num_estimators = int(kwargs['0'])
+ maxDepth = int(kwargs['1'])
+ classifier = RandomForestClassifier(n_estimators=num_estimators, max_depth=maxDepth, n_jobs=NB_CORES)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+
+ # PipeLine with RandomForest classifier
+ pipeline_rf = Pipeline([('classifier', RandomForestClassifier())])
+
+ # Parameters for GridSearch: Number of Trees
+ # can be extended with: oob_score, min_samples_leaf, max_features
+ param_rf = {"classifier__n_estimators": map(int, kwargs['0'])}
+
+ # pipeline: Gridsearch avec le pipeline comme estimator
+ # param: pour obtenir le meilleur model il va essayer tous les possiblites
+ # refit: pour utiliser le meilleur model apres girdsearch
+ # n_jobs: Nombre de CPU (Mon ordi a des problemes avec -1 (Bug Python 2.7 sur Windows))
+ # scoring: scoring...
+ # cv: Nombre de K-Folds pour CV
+ grid_rf = GridSearchCV(
+ pipeline_rf,
+ param_grid=param_rf,
+ refit=True,
+ n_jobs=nbCores,
+ scoring='accuracy',
+ cv=nbFolds,
+ )
+
+ rf_detector = grid_rf.fit(X_train, y_train)
+
+ desc_estimators = [rf_detector.best_params_["classifier__n_estimators"]]
+ description = "Classif_" + "RF" + "-" + "CV_" + str(nbFolds) + "-" + "Trees_" + str(map(str,desc_estimators))
+ return description, rf_detector
+
+
+def getConfig(config):
+ return "\n\t\t- Random Forest with num_esimators : "+config[0]+", max_depth : "+config[1]
\ No newline at end of file
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SGD.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SGD.py
new file mode 100644
index 0000000000000000000000000000000000000000..3a2bc27f097a3503fa09a4ac4ad34255dcd2da11
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SGD.py
@@ -0,0 +1,32 @@
+from sklearn.linear_model import SGDClassifier
+from sklearn.pipeline import Pipeline # Pipelining in classification
+from sklearn.grid_search import GridSearchCV
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
+ loss = kwargs['0']
+ penalty = kwargs['1']
+ try:
+ alpha = int(kwargs['2'])
+ except:
+ alpha = 0.15
+ classifier = SGDClassifier(loss=loss, penalty=penalty, alpha=alpha)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_SGD = Pipeline([('classifier', SGDClassifier())])
+ param_SGD = {"classifier__loss": kwargs['1'], "classifier__penalty": kwargs['2'],
+ "classifier__alpha": map(float, kwargs['0'])}
+ grid_SGD = GridSearchCV(pipeline_SGD, param_grid=param_SGD, refit=True, n_jobs=nbCores, scoring='accuracy',
+ cv=nbFolds)
+ SGD_detector = grid_SGD.fit(X_train, y_train)
+ desc_params = [SGD_detector.best_params_["classifier__loss"], SGD_detector.best_params_["classifier__penalty"],
+ SGD_detector.best_params_["classifier__alpha"]]
+ description = "Classif_" + "Lasso" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
+ return description, SGD_detector
+
+
+def getConfig(config):
+ return "\n\t\t- SGDClassifier with loss : "+config[0]+", penalty : "+config[1]
\ No newline at end of file
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMLinear.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMLinear.py
new file mode 100644
index 0000000000000000000000000000000000000000..568badb41da2130e116459ba4123d47b3430befa
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMLinear.py
@@ -0,0 +1,25 @@
+from sklearn.svm import SVC
+from sklearn.pipeline import Pipeline # Pipelining in classification
+from sklearn.grid_search import GridSearchCV
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
+ C = int(kwargs['0'])
+ classifier = SVC(C=C, kernel='linear', probability=True)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_SVMLinear = Pipeline([('classifier', SVC(kernel="linear"))])
+ param_SVMLinear = {"classifier__C": map(int, kwargs['0'])}
+ grid_SVMLinear = GridSearchCV(pipeline_SVMLinear, param_grid=param_SVMLinear, refit=True, n_jobs=nbCores, scoring='accuracy',
+ cv=nbFolds)
+ SVMLinear_detector = grid_SVMLinear.fit(X_train, y_train)
+ desc_params = [SVMLinear_detector.best_params_["classifier__C"]]
+ description = "Classif_" + "SVC" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
+ return description, SVMLinear_detector
+
+
+def getConfig(config):
+ return "\n\t\t- SVM with C : "+config[0]+", kernel : "+config[1]
\ No newline at end of file
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMPoly.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMPoly.py
new file mode 100644
index 0000000000000000000000000000000000000000..9f43f0b9417e7defb873a384b25d4a676f15b50f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMPoly.py
@@ -0,0 +1,26 @@
+from sklearn.svm import SVC
+from sklearn.pipeline import Pipeline # Pipelining in classification
+from sklearn.grid_search import GridSearchCV
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
+ C = int(kwargs['0'])
+ degree = int(kwargs['1'])
+ classifier = SVC(C=C, kernel='poly', degree=degree, probability=True)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_SVMLinear = Pipeline([('classifier', SVC(kernel="linear"))])
+ param_SVMLinear = {"classifier__C": map(int, kwargs['0']), "classifier__degree": map(int, kwargs["1"])}
+ grid_SVMLinear = GridSearchCV(pipeline_SVMLinear, param_grid=param_SVMLinear, refit=True, n_jobs=nbCores, scoring='accuracy',
+ cv=nbFolds)
+ SVMLinear_detector = grid_SVMLinear.fit(X_train, y_train)
+ desc_params = [SVMLinear_detector.best_params_["classifier__C"], SVMLinear_detector.best_params_["classifier__degree"]]
+ description = "Classif_" + "SVC" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
+ return description, SVMLinear_detector
+
+
+def getConfig(config):
+ return "\n\t\t- SVM with C : "+config[0]+", kernel : "+config[1]
\ No newline at end of file
diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMRBF.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMRBF.py
new file mode 100644
index 0000000000000000000000000000000000000000..202cc076a9a92223b92626334d38f2ae67515c64
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SVMRBF.py
@@ -0,0 +1,25 @@
+from sklearn.svm import SVC
+from sklearn.pipeline import Pipeline # Pipelining in classification
+from sklearn.grid_search import GridSearchCV
+
+
+def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
+ C = int(kwargs['0'])
+ classifier = SVC(C=C, kernel='rbf', probability=True)
+ classifier.fit(DATASET, CLASS_LABELS)
+ return classifier
+
+
+def fit_gridsearch(X_train, y_train, nbFolds=4, nbCores=1, **kwargs):
+ pipeline_SVMRBF = Pipeline([('classifier', SVC(kernel="rbf"))])
+ param_SVMRBF = {"classifier__C": map(int, kwargs['0'])}
+ grid_SVMRBF = GridSearchCV(pipeline_SVMRBF, param_grid=param_SVMRBF, refit=True, n_jobs=nbCores, scoring='accuracy',
+ cv=nbFolds)
+ SVMRBF_detector = grid_SVMRBF.fit(X_train, y_train)
+ desc_params = [SVMRBF_detector.best_params_["classifier__C"]]
+ description = "Classif_" + "SVC" + "-" + "CV_" + str(nbFolds) + "-" + "-".join(map(str,desc_params))
+ return description, SVMRBF_detector
+
+
+def getConfig(config):
+ return "\n\t\t- SVM with C : "+config[0]+", kernel : "+config[1]
\ No newline at end of file
diff --git a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/__init__.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/__init__.py
similarity index 100%
rename from Code/Multiview/Fusion/Methods/MonoviewClassifiers/__init__.py
rename to Code/MonoMutliViewClassifiers/MonoviewClassifiers/__init__.py
diff --git a/Code/Multiview/ExecMultiview.py b/Code/MonoMutliViewClassifiers/Multiview/ExecMultiview.py
similarity index 93%
rename from Code/Multiview/ExecMultiview.py
rename to Code/MonoMutliViewClassifiers/Multiview/ExecMultiview.py
index ebc61a5bf3b3ddb37c202cc2eff975ccd8aa8310..cffd6f0199454f50c0e589ba7b48216a020aba20 100644
--- a/Code/Multiview/ExecMultiview.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/ExecMultiview.py
@@ -15,6 +15,7 @@ import logging
import time
+
def ExecMultiview(DATASET, name, learningRate, nbFolds, nbCores, databaseType, path, LABELS_DICTIONARY, gridSearch=False, **kwargs):
datasetLength = DATASET.get("Metadata").attrs["datasetLength"]
@@ -26,8 +27,7 @@ def ExecMultiview(DATASET, name, learningRate, nbFolds, nbCores, databaseType, p
views = kwargs["views"]
NB_VIEW = kwargs["NB_VIEW"]
LABELS_NAMES = kwargs["LABELS_NAMES"]
- MumboKWARGS = kwargs["MumboKWARGS"]
- FusionKWARGS = kwargs["FusionKWARGS"]
+ classificationKWARGS = kwargs[CL_type+"KWARGS"]
t_start = time.time()
logging.info("### Main Programm for Multiview Classification")
@@ -78,8 +78,8 @@ def ExecMultiview(DATASET, name, learningRate, nbFolds, nbCores, databaseType, p
if gridSearch:
logging.info("Start:\t Gridsearching best settings for monoview classifiers")
- bestSettings = classifierGridSearch(DATASET, initKWARGS["classifiersNames"])
- initKWARGS["classifiersConfigs"] = bestSettings
+ bestSettings = classifierGridSearch(DATASET, classificationKWARGS["classifiersNames"])
+ classificationKWARGS["classifiersConfigs"] = bestSettings
logging.info("Done:\t Gridsearching best settings for monoview classifiers")
# Begin Classification
@@ -89,7 +89,7 @@ def ExecMultiview(DATASET, name, learningRate, nbFolds, nbCores, databaseType, p
logging.info("\tStart:\t Fold number " + str(foldIdx + 1))
trainIndices = [index for index in range(datasetLength) if index not in fold]
DATASET_LENGTH = len(trainIndices)
- classifier = classifierClass(NB_VIEW, DATASET_LENGTH, DATASET.get("labels").value, NB_CORES=nbCores, **initKWARGS)
+ classifier = classifierClass(NB_VIEW, DATASET_LENGTH, DATASET.get("labels").value, NB_CORES=nbCores, **classificationKWARGS)
classifier.fit_hdf5(DATASET, trainIndices=trainIndices)
kFoldClassifier.append(classifier)
@@ -149,6 +149,9 @@ if __name__=='__main__':
parser = argparse.ArgumentParser(
description='This file is used to classifiy multiview data thanks to three methods : Fusion (early & late), Multiview Machines, Mumbo.',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+ # create the top-level parser
+
+
groupStandard = parser.add_argument_group('Standard arguments')
groupStandard.add_argument('-log', action='store_true', help='Use option to activate Logging to Console')
@@ -183,12 +186,14 @@ if __name__=='__main__':
help='Determine which monoview classifier to use with Mumbo',
default='DecisionTree:DecisionTree:DecisionTree:DecisionTree')
groupMumbo.add_argument('--MU_config', metavar='STRING', action='store', nargs='+',
- help='Configuration for the monoview classifier in Mumbo', default=['1:0.02', '1:0.018', '1:0.1',
+ help='Configuration for the monoview classifier in Mumbo', default=['1:0.02', '1:0.018',
+ '1:0.1',
'2:0.09'])
- groupMumbo.add_argument('--MU_iter', metavar='INT', action='store',
- help='Number of iterations in Mumbos learning process', type=int, default=5)
+ groupMumbo.add_argument('--MU_iter', metavar='INT', action='store', nargs=3,
+ help='Max number of iteration, min number of iteration, convergeance threshold', type=float,
+ default=[1000,300,0.0005])
- groupFusion = parser.add_argument_group('Fusion arguments')
+ groupFusion = parser.add_argument_group('Fusion', "poulet")
groupFusion.add_argument('--FU_type', metavar='STRING', action='store',
help='Determine which type of fusion to use', default='LateFusion')
groupFusion.add_argument('--FU_method', metavar='STRING', action='store',
@@ -201,8 +206,9 @@ if __name__=='__main__':
groupFusion.add_argument('--FU_cl_config', metavar='STRING', action='store', nargs='+',
help='Configuration for the monoview classifiers used', default=['3:4', 'log:l2', '10:linear',
'4'])
-
+ print parser
args = parser.parse_args()
+ print args
views = args.views.split(":")
dataBaseType = args.type
NB_VIEW = len(views)
@@ -213,7 +219,6 @@ if __name__=='__main__':
NB_CLASS = args.CL_nb_class
LABELS_NAMES = args.CL_classes.split(":")
mumboclassifierNames = args.MU_type.split(':')
- mumboNB_ITER = args.MU_iter
NB_CORES = args.CL_cores
fusionClassifierNames = args.FU_cl_names.split(":")
fusionClassifierConfig = [argument.split(':') for argument in args.FU_cl_config]
@@ -221,7 +226,9 @@ if __name__=='__main__':
FusionKWARGS = {"fusionType":args.FU_type, "fusionMethod":args.FU_method,
"classifiersNames":fusionClassifierNames, "classifiersConfigs":fusionClassifierConfig,
'fusionMethodConfig':fusionMethodConfig}
- MumboKWARGS = {"classifiersConfigs":mumboClassifierConfig, "NB_ITER":mumboNB_ITER, "classifiersNames":mumboclassifierNames}
+ MumboKWARGS = {"classifiersConfigs":mumboClassifierConfig,
+ "classifiersNames":mumboclassifierNames, "maxIter":int(args.MU_iter[0]),
+ "minIter":int(args.MU_iter[1]), "threshold":args.MU_iter[2]}
dir = os.path.dirname(os.path.abspath(__file__)) + "/Results/"
logFileName = time.strftime("%Y%m%d-%H%M%S") + "-CMultiV-" + args.CL_type + "-" + "_".join(views) + "-" + args.name + \
"-LOG"
@@ -252,10 +259,10 @@ if __name__=='__main__':
DATASET, LABELS_DICTIONARY = getDatabase(views, args.pathF, args.name, NB_CLASS, LABELS_NAMES)
logging.info("Info:\t Labels used: " + ", ".join(LABELS_DICTIONARY.values()))
- logging.info("Info:\t Length of dataset:" + str(DATASET.get("Metadata").attrs["datasetlength"]))
+ logging.info("Info:\t Length of dataset:" + str(DATASET.get("Metadata").attrs["datasetLength"]))
ExecMultiview(DATASET, args.name, args.CL_split, args.CL_nbFolds, args.CL_cores, args.type, args.pathF,
- LABELS_DICTIONARY, gridSearch=True, **arguments)
+ LABELS_DICTIONARY, gridSearch=False, **arguments)
diff --git a/Code/Multiview/Fusion/Fusion.py b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Fusion.py
similarity index 100%
rename from Code/Multiview/Fusion/Fusion.py
rename to Code/MonoMutliViewClassifiers/Multiview/Fusion/Fusion.py
diff --git a/Code/Multiview/Fusion/Methods/EarlyFusion.py b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/EarlyFusion.py
similarity index 97%
rename from Code/Multiview/Fusion/Methods/EarlyFusion.py
rename to Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/EarlyFusion.py
index 761d1b4ce61953577e68ba4b48a0289cc33eaa97..dd86041d22dc90f66908ac26afe2805b2154812d 100644
--- a/Code/Multiview/Fusion/Methods/EarlyFusion.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/EarlyFusion.py
@@ -1,10 +1,10 @@
#!/usr/bin/env python
# -*- encoding: utf-8
-import MonoviewClassifiers
-
import numpy as np
+import MonoviewClassifiers
+
class EarlyFusionClassifier(object):
def __init__(self, monoviewClassifiersNames, monoviewClassifiersConfigs, NB_CORES=1):
@@ -56,7 +56,7 @@ class WeightedLinear(EarlyFusionClassifier):
def getConfig(self, fusionMethodConfig ,monoviewClassifiersNames, monoviewClassifiersConfigs):
configString = "with weighted concatenation, using weights : "+", ".join(map(str, self.weights))+\
" with monoview classifier : "
- monoviewClassifierModule = getattr(MonoviewClassifiers, monoviewClassifiersNames[0])
+ monoviewClassifierModule = getattr(poulet, monoviewClassifiersNames[0])
configString += monoviewClassifierModule.getConfig(monoviewClassifiersConfigs[0])
return configString
diff --git a/Code/Multiview/Fusion/Methods/LateFusion.py b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/LateFusion.py
similarity index 99%
rename from Code/Multiview/Fusion/Methods/LateFusion.py
rename to Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/LateFusion.py
index 962f51b07e8af4c32b6ec5e5f4ffc95908456238..9222d7339935418485a66e4c55ad1dbd04042474 100644
--- a/Code/Multiview/Fusion/Methods/LateFusion.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/LateFusion.py
@@ -2,11 +2,11 @@
# -*- encoding: utf-8
import numpy as np
-import sys
-from sklearn.svm import SVC
+from joblib import Parallel, delayed
from sklearn.multiclass import OneVsOneClassifier
+from sklearn.svm import SVC
+
import MonoviewClassifiers
-from joblib import Parallel, delayed
# Our method in multiclass classification will be One-vs-One or One-vs-All
diff --git a/Code/Multiview/Fusion/Methods/__init__.py b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/__init__.py
similarity index 100%
rename from Code/Multiview/Fusion/Methods/__init__.py
rename to Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/__init__.py
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/poulet/__init__.py b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/poulet/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..9bbd76fbbcd47eb690b8c69a78695d7ef7ab1660
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Fusion/Methods/poulet/__init__.py
@@ -0,0 +1,7 @@
+import os
+for module in os.listdir(os.path.dirname(os.path.realpath(__file__))):
+ if module == '__init__.py' or module[-3:] != '.py':
+ continue
+ __import__(module[:-3], locals(), globals())
+del module
+del os
\ No newline at end of file
diff --git a/Code/Multiview/Fusion/__init__.py b/Code/MonoMutliViewClassifiers/Multiview/Fusion/__init__.py
similarity index 100%
rename from Code/Multiview/Fusion/__init__.py
rename to Code/MonoMutliViewClassifiers/Multiview/Fusion/__init__.py
diff --git a/Code/Multiview/Fusion/analyzeResults.py b/Code/MonoMutliViewClassifiers/Multiview/Fusion/analyzeResults.py
similarity index 100%
rename from Code/Multiview/Fusion/analyzeResults.py
rename to Code/MonoMutliViewClassifiers/Multiview/Fusion/analyzeResults.py
diff --git a/Code/Multiview/GetMultiviewDb.py b/Code/MonoMutliViewClassifiers/Multiview/GetMultiviewDb.py
similarity index 99%
rename from Code/Multiview/GetMultiviewDb.py
rename to Code/MonoMutliViewClassifiers/Multiview/GetMultiviewDb.py
index 8a9dfa82e61ea17cdd3152f2068f277d19fbe749..b839496fd441750d60f60d2eb9550905973acf8c 100644
--- a/Code/Multiview/GetMultiviewDb.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/GetMultiviewDb.py
@@ -145,7 +145,6 @@ def getKFoldIndices(nbFolds, CLASS_LABELS, NB_CLASS, learningIndices):
for foldIndex, fold in enumerate(nbTrainingExamples):
trainingExamplesIndices.append([])
while fold != [0 for i in range(NB_CLASS)]:
- print fold
index = random.randint(0, len(learningIndices)-1)
if learningIndices[index] not in usedIndices:
isUseFull, fold = isUseful(fold, learningIndices[index], CLASS_LABELS, labelDict)
@@ -327,7 +326,7 @@ def getMultiOmicDBcsv(features, path, name, NB_CLASS, LABELS_NAMES):
rnaseqData = np.genfromtxt(path+"matching_rnaseq.csv", delimiter=',')
rnaseqDset = datasetFile.create_dataset("View2", rnaseqData.shape)
rnaseqDset[...] = rnaseqData
- rnaseqDset.attrs["name"]="RANSeq"
+ rnaseqDset.attrs["name"]="RNASeq"
logging.debug("Done:\t Getting RNASeq Data")
logging.debug("Start:\t Getting Clinical Data")
@@ -376,7 +375,7 @@ def getModifiedMultiOmicDBcsv(features, path, name, NB_CLASS, LABELS_NAMES):
rnaseqData = np.genfromtxt(path+"matching_rnaseq.csv", delimiter=',')
rnaseqDset = datasetFile.create_dataset("View2", rnaseqData.shape)
rnaseqDset[...] = rnaseqData
- rnaseqDset.attrs["name"]="RANSeq_"
+ rnaseqDset.attrs["name"]="RNASeq_"
logging.debug("Done:\t Getting RNASeq Data")
logging.debug("Start:\t Getting Clinical Data")
diff --git a/Code/Multiview/Mumbo/Classifiers/DecisionTree.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/DecisionTree.py
similarity index 95%
rename from Code/Multiview/Mumbo/Classifiers/DecisionTree.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/DecisionTree.py
index 8a087b766d0604627a265367799ff0a6cb69b5cf..2981081de25a515c7055d3f12155f37c3eea0df9 100644
--- a/Code/Multiview/Mumbo/Classifiers/DecisionTree.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/DecisionTree.py
@@ -3,6 +3,7 @@ from sklearn.metrics import precision_recall_fscore_support, accuracy_score
import numpy as np
from ModifiedMulticlass import OneVsRestClassifier
from SubSampling import subSample
+import logging
# Add weights
def DecisionTree(data, labels, arg, weights):
@@ -105,8 +106,11 @@ def getBestSetting(bestSettings, bestResults):
diffTo52 = 100.0
bestSettingsIndex = 0
for resultIndex, result in enumerate(bestResults):
- if abs(52.5-result)<diffTo52:
+ if abs(0.55-result) < diffTo52:
+ diffTo52 = abs(0.55-result)
+ bestResult = result
bestSettingsIndex = resultIndex
+ logging.debug("\t\tInfo:\t Best Reslut : "+str(result))
return map(lambda p: round(p, 4), bestSettings[bestSettingsIndex])
-# return map(round(,4), bestSettings[bestSettingsIndex])
\ No newline at end of file
+ # return map(round(,4), bestSettings[bestSettingsIndex])
\ No newline at end of file
diff --git a/Code/Multiview/Mumbo/Classifiers/Kover.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/Kover.py
similarity index 100%
rename from Code/Multiview/Mumbo/Classifiers/Kover.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/Kover.py
diff --git a/Code/Multiview/Mumbo/Classifiers/ModifiedMulticlass.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/ModifiedMulticlass.py
similarity index 100%
rename from Code/Multiview/Mumbo/Classifiers/ModifiedMulticlass.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/ModifiedMulticlass.py
diff --git a/Code/Multiview/Mumbo/Classifiers/SubSampling.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/SubSampling.py
similarity index 100%
rename from Code/Multiview/Mumbo/Classifiers/SubSampling.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/SubSampling.py
diff --git a/Code/Multiview/Mumbo/Classifiers/__init__.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/__init__.py
similarity index 100%
rename from Code/Multiview/Mumbo/Classifiers/__init__.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/Classifiers/__init__.py
diff --git a/Code/Multiview/Mumbo/Mumbo.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Mumbo.py
similarity index 84%
rename from Code/Multiview/Mumbo/Mumbo.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/Mumbo.py
index 912d6ebab17eb2160e0c69ec9d179bdbe808d900..20e1e9613077937c0a8a463ad91213812156a843 100644
--- a/Code/Multiview/Mumbo/Mumbo.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/Mumbo.py
@@ -2,7 +2,10 @@ import numpy as np
import math
from joblib import Parallel, delayed
from Classifiers import *
+import time
import logging
+import matplotlib.pyplot as plt
+from sklearn.metrics import accuracy_score
# Data shape : ((Views, Examples, Corrdinates))
@@ -23,8 +26,7 @@ def trainWeakClassifier(classifierName, monoviewDataset, CLASS_LABELS,
weights = computeWeights(DATASET_LENGTH, iterIndex, viewIndice, CLASS_LABELS, costMatrices)
classifierModule = globals()[classifierName] # Permet d'appeler une fonction avec une string
classifierMethod = getattr(classifierModule, classifierName)
- classifier, classes, isBad, pTr = classifierMethod(monoviewDataset, CLASS_LABELS, classifier_config, weights)
- averageAccuracy = np.mean(pTr)
+ classifier, classes, isBad, averageAccuracy = classifierMethod(monoviewDataset, CLASS_LABELS, classifier_config, weights)
logging.debug("\t\t\tView " + str(viewIndice) + " : " + str(averageAccuracy))
return classifier, classes, isBad, averageAccuracy
@@ -33,18 +35,19 @@ def trainWeakClassifier_hdf5(classifierName, monoviewDataset, CLASS_LABELS, DATA
weights = computeWeights(DATASET_LENGTH, iterIndex, viewIndice, CLASS_LABELS, costMatrices)
classifierModule = globals()[classifierName] # Permet d'appeler une fonction avec une string
classifierMethod = getattr(classifierModule, classifierName)
- classifier, classes, isBad, pTr = classifierMethod(monoviewDataset, CLASS_LABELS, classifier_config, weights)
- averageAccuracy = np.mean(pTr)
+ classifier, classes, isBad, averageAccuracy = classifierMethod(monoviewDataset, CLASS_LABELS, classifier_config, weights)
logging.debug("\t\t\tView " + str(viewIndice) + " : " + str(averageAccuracy))
return classifier, classes, isBad, averageAccuracy
def gridSearch_hdf5(DATASET, classifiersNames):
bestSettings = []
for classifierIndex, classifierName in enumerate(classifiersNames):
+ logging.debug("\tStart:\t Gridsearch for "+classifierName+" on "+DATASET.get("View"+str(classifierIndex)).attrs["name"])
classifierModule = globals()[classifierName] # Permet d'appeler une fonction avec une string
classifierMethod = getattr(classifierModule, "gridSearch")
bestSettings.append(classifierMethod(DATASET.get("View"+str(classifierIndex))[...],
DATASET.get("labels")[...]))
+ logging.debug("\tDone:\t Gridsearch for "+classifierName)
return bestSettings
@@ -54,43 +57,45 @@ def gridSearch_hdf5(DATASET, classifiersNames):
class Mumbo:
def __init__(self, NB_VIEW, DATASET_LENGTH, CLASS_LABELS, NB_CORES=1,**kwargs):
- self.nbIter = kwargs["NB_ITER"]
+ self.maxIter = kwargs["maxIter"]
+ self.minIter = kwargs["minIter"]
+ self.threshold = kwargs["threshold"]
self.classifiersNames = kwargs["classifiersNames"]
self.classifiersConfigs = kwargs["classifiersConfigs"]
nbClass = len(set(CLASS_LABELS))
- self.nbIter = kwargs["NB_ITER"]
self.costMatrices = np.array([
- np.array([
- np.array([
- np.array([1 if CLASS_LABELS[exampleIndice] != classe
- else -(nbClass - 1)
- for classe in range(nbClass)
- ]) for exampleIndice in range(DATASET_LENGTH)
- ]) for viewIndice in range(NB_VIEW)])
- if iteration == 0
- else np.zeros((NB_VIEW, DATASET_LENGTH, nbClass))
- for iteration in range(self.nbIter + 1)
- ])
+ np.array([
+ np.array([
+ np.array([1 if CLASS_LABELS[exampleIndice] != classe
+ else -(nbClass - 1)
+ for classe in range(nbClass)
+ ]) for exampleIndice in range(DATASET_LENGTH)
+ ]) for viewIndice in range(NB_VIEW)])
+ if iteration == 0
+ else np.zeros((NB_VIEW, DATASET_LENGTH, nbClass))
+ for iteration in range(self.maxIter + 1)
+ ])
self.generalCostMatrix = np.array([
np.array([
np.array([1 if CLASS_LABELS[exampleIndice] != classe
else -(nbClass - 1)
for classe in range(nbClass)
]) for exampleIndice in range(DATASET_LENGTH)
- ]) for iteration in range(self.nbIter)
+ ]) for iteration in range(self.maxIter)
])
- self.fs = np.zeros((self.nbIter, NB_VIEW, DATASET_LENGTH, nbClass))
- self.ds = np.zeros((self.nbIter, NB_VIEW, DATASET_LENGTH))
- self.edges = np.zeros((self.nbIter, NB_VIEW))
- self.alphas = np.zeros((self.nbIter, NB_VIEW))
- self.predictions = np.zeros((self.nbIter, NB_VIEW, DATASET_LENGTH))
- self.generalAlphas = np.zeros(self.nbIter)
- self.generalFs = np.zeros((self.nbIter, DATASET_LENGTH, nbClass))
+ self.fs = np.zeros((self.maxIter, NB_VIEW, DATASET_LENGTH, nbClass))
+ self.ds = np.zeros((self.maxIter, NB_VIEW, DATASET_LENGTH))
+ self.edges = np.zeros((self.maxIter, NB_VIEW))
+ self.alphas = np.zeros((self.maxIter, NB_VIEW))
+ self.predictions = np.zeros((self.maxIter, NB_VIEW, DATASET_LENGTH))
+ self.generalAlphas = np.zeros(self.maxIter)
+ self.generalFs = np.zeros((self.maxIter, DATASET_LENGTH, nbClass))
self.nbCores = NB_CORES
self.iterIndex = 0
self.bestClassifiers = []
- self.bestViews = np.zeros(self.nbIter, dtype=int)
- self.averageAccuracies = np.zeros((self.nbIter, NB_VIEW))
+ self.bestViews = np.zeros(self.maxIter, dtype=int)
+ self.averageAccuracies = np.zeros((self.maxIter, NB_VIEW))
+ self.iterAccuracies = np.zeros(self.maxIter)
# costMatrices = np.array([
# np.array([
# np.array([
@@ -134,17 +139,23 @@ class Mumbo:
# predictions, generalAlphas, generalFs = initialize(NB_CLASS, NB_VIEW,
# NB_ITER, DATASET_LENGTH,
# LABELS[trainIndices])
- bestViews = np.zeros(self.nbIter)
+ bestViews = np.zeros(self.maxIter)
bestClassifiers = []
# Learning
+ isStabilized=False
self.iterIndex = 0
- for i in range(self.nbIter):
+ while not isStabilized or self.iterIndex >= self.maxIter:
+ if self.iterIndex > self.minIter:
+ coeffs = np.polyfit(np.log(np.arange(self.iterIndex)+0.00001), self.iterAccuracies[:self.iterIndex], 1)
+ if coeffs[0]/self.iterIndex < self.threshold:
+ isStabilized = True
+
logging.debug('\t\tStart:\t Iteration ' + str(self.iterIndex + 1))
classifiers, predictedLabels, areBad = self.trainWeakClassifiers_hdf5(DATASET, trainIndices, NB_CLASS,
DATASET_LENGTH, NB_VIEW)
if areBad.all():
- logging.warning("All bad for iteration " + str(self.iterIndex))
+ logging.warning("WARNING:\tAll bad for iteration " + str(self.iterIndex))
self.predictions[self.iterIndex] = predictedLabels
@@ -169,6 +180,10 @@ class Mumbo:
self.bestClassifiers.append(classifiers[bestView])
self.updateGeneralFs(DATASET_LENGTH, NB_CLASS, bestView)
self.updateGeneralCostMatrix(DATASET_LENGTH, NB_CLASS,LABELS)
+ predictedLabels = self.predict_hdf5(DATASET, usedIndices=trainIndices)
+ accuracy = accuracy_score(DATASET.get("labels")[trainIndices], predictedLabels)
+ self.iterAccuracies[self.iterIndex] = accuracy
+
self.iterIndex += 1
# finalFs = computeFinalFs(DATASET_LENGTH, NB_CLASS, generalAlphas, predictions, bestViews, LABELS, NB_ITER)
@@ -184,7 +199,7 @@ class Mumbo:
for labelIndex, exampleIndex in enumerate(usedIndices):
votes = np.zeros(NB_CLASS)
for classifier, alpha, view in zip(self.bestClassifiers, self.alphas, self.bestViews):
- data = DATASET["/View"+str(int(view))+"/matrix"][exampleIndex, :]
+ data = DATASET["/View"+str(int(view))][exampleIndex, :]
votes[int(classifier.predict(np.array([data])))] += alpha[view]
predictedLabels[labelIndex] = np.argmax(votes)
else:
@@ -204,10 +219,10 @@ class Mumbo:
classifiersNames = self.classifiersNames
iterIndex = self.iterIndex
trainedClassifiersAndLabels = Parallel(n_jobs=NB_JOBS)(
- delayed(trainWeakClassifier)(classifiersNames[viewIndice], DATASET[viewIndice], CLASS_LABELS,
- DATASET_LENGTH, viewIndice, classifiersConfigs[viewIndice], iterIndex,
- costMatrices)
- for viewIndice in range(NB_VIEW))
+ delayed(trainWeakClassifier)(classifiersNames[viewIndice], DATASET[viewIndice], CLASS_LABELS,
+ DATASET_LENGTH, viewIndice, classifiersConfigs[viewIndice], iterIndex,
+ costMatrices)
+ for viewIndice in range(NB_VIEW))
for viewIndex, (classifier, labelsArray, isBad, averageAccuracy) in enumerate(trainedClassifiersAndLabels):
self.averageAccuracies[self.iterIndex, viewIndex] = averageAccuracy
@@ -217,7 +232,7 @@ class Mumbo:
return np.array(trainedClassifiers), np.array(labelsMatrix), np.array(areBad)
def trainWeakClassifiers_hdf5(self, DATASET, trainIndices, NB_CLASS,
- DATASET_LENGTH, NB_VIEW):
+ DATASET_LENGTH, NB_VIEW):
trainedClassifiers = []
labelsMatrix = []
areBad = []
@@ -230,13 +245,13 @@ class Mumbo:
classifiersNames = self.classifiersNames
iterIndex = self.iterIndex
trainedClassifiersAndLabels = Parallel(n_jobs=NB_JOBS)(
- delayed(trainWeakClassifier_hdf5)(classifiersNames[viewIndex],
- DATASET.get("View"+str(viewIndex))[trainIndices, :],
- DATASET.get("labels")[trainIndices],
- DATASET_LENGTH,
- viewIndex, classifiersConfigs[viewIndex],
- DATASET.get("View"+str(viewIndex)).attrs["name"], iterIndex, costMatrices)
- for viewIndex in range(NB_VIEW))
+ delayed(trainWeakClassifier_hdf5)(classifiersNames[viewIndex],
+ DATASET.get("View"+str(viewIndex))[trainIndices, :],
+ DATASET.get("labels")[trainIndices],
+ DATASET_LENGTH,
+ viewIndex, classifiersConfigs[viewIndex],
+ DATASET.get("View"+str(viewIndex)).attrs["name"], iterIndex, costMatrices)
+ for viewIndex in range(NB_VIEW))
for viewIndex, (classifier, labelsArray, isBad, averageAccuracy) in enumerate(trainedClassifiersAndLabels):
self.averageAccuracies[self.iterIndex, viewIndex] = averageAccuracy
@@ -250,11 +265,11 @@ class Mumbo:
costMatrix = self.costMatrices[self.iterIndex, viewIndex]
# return np.sum(np.array([np.sum(predictionMatrix*costMatrix[:,classIndice]) for classIndice in range(NB_CLASS)]))
cCost = float(np.sum(np.array(
- [costMatrix[exampleIndice, int(predictionMatrix[exampleIndice])] for exampleIndice in
- range(DATASET_LENGTH)])))
+ [costMatrix[exampleIndice, int(predictionMatrix[exampleIndice])] for exampleIndice in
+ range(DATASET_LENGTH)])))
tCost = float(np.sum(
- np.array([-costMatrix[exampleIndice, CLASS_LABELS[exampleIndice]] for exampleIndice in
- range(DATASET_LENGTH)])))
+ np.array([-costMatrix[exampleIndice, CLASS_LABELS[exampleIndice]] for exampleIndice in
+ range(DATASET_LENGTH)])))
if tCost == 0.:
self.edges[self.iterIndex, viewIndex] = -cCost
else:
@@ -283,13 +298,13 @@ class Mumbo:
== \
CLASS_LABELS[exampleIndice] \
or self.allViewsClassifyWell(self.predictions, pastIterIndice,
- NB_VIEW, CLASS_LABELS[exampleIndice],
- exampleIndice):
+ NB_VIEW, CLASS_LABELS[exampleIndice],
+ exampleIndice):
self.ds[pastIterIndice, viewIndice, exampleIndice] = 1
else:
self.ds[pastIterIndice, viewIndice, exampleIndice] = 0
- #return ds
+ #return ds
def updateFs(self, NB_VIEW, DATASET_LENGTH, NB_CLASS):
for viewIndice in range(NB_VIEW):
@@ -299,14 +314,14 @@ class Mumbo:
= np.sum(np.array([self.alphas[pastIterIndice, viewIndice]
* self.ds[pastIterIndice, viewIndice, exampleIndice]
if self.predictions[pastIterIndice, viewIndice,
- exampleIndice]
+ exampleIndice]
==
classe
else 0
for pastIterIndice in range(self.iterIndex)]))
if np.amax(np.absolute(self.fs)) != 0:
self.fs /= np.amax(np.absolute(self.fs))
- #return fs
+ #return fs
def updateCostmatrices(self, NB_VIEW, DATASET_LENGTH, NB_CLASS, CLASS_LABELS):
for viewIndice in range(NB_VIEW):
@@ -336,8 +351,8 @@ class Mumbo:
self.generalFs[self.iterIndex, exampleIndice, classe] \
= np.sum(np.array([self.generalAlphas[pastIterIndice]
if self.predictions[pastIterIndice,
- bestView,
- exampleIndice]
+ bestView,
+ exampleIndice]
==
classe
else 0
@@ -346,7 +361,7 @@ class Mumbo:
)
if np.amax(np.absolute(self.generalFs)) != 0:
self.generalFs /= np.amax(np.absolute(self.generalFs))
- #return generalFs
+ #return generalFs
def updateGeneralCostMatrix(self, DATASET_LENGTH, NB_CLASS, CLASS_LABELS):
for exampleIndice in range(DATASET_LENGTH):
@@ -359,8 +374,8 @@ class Mumbo:
self.generalCostMatrix[self.iterIndex, exampleIndice, classe] \
= -1 * np.sum(np.exp(self.generalFs[self.iterIndex, exampleIndice] -
self.generalFs[self.iterIndex, exampleIndice, classe]))
- # if np.amax(np.absolute(generalCostMatrix)) != 0:
- # generalCostMatrix = generalCostMatrix/np.amax(np.absolute(generalCostMatrix))
+ # if np.amax(np.absolute(generalCostMatrix)) != 0:
+ # generalCostMatrix = generalCostMatrix/np.amax(np.absolute(generalCostMatrix))
def fit(self, DATASET, CLASS_LABELS, **kwargs):
# Initialization
@@ -372,11 +387,11 @@ class Mumbo:
# predictions, generalAlphas, generalFs = initialize(NB_CLASS, NB_VIEW,
# NB_ITER, DATASET_LENGTH,
# CLASS_LABELS)
- bestViews = np.zeros(self.nbIter)
+ bestViews = np.zeros(self.maxIter)
bestClassifiers = []
# Learning
- for i in range(self.nbIter):
+ for i in range(self.maxIter):
logging.debug('\t\tStart:\t Iteration ' + str(self.iterIndex + 1))
classifiers, predictedLabels, areBad = self.trainWeakClassifiers(DATASET, CLASS_LABELS, NB_CLASS,
DATASET_LENGTH, NB_VIEW)
@@ -391,7 +406,7 @@ class Mumbo:
self.alphas[self.iterIndex, viewIndice] = 0.
else:
self.alphas[self.iterIndex, viewIndice] = self.computeAlpha(self.edges[self.iterIndex,
- viewIndice])
+ viewIndice])
self.updateDs(CLASS_LABELS, NB_VIEW, DATASET_LENGTH)
self.updateFs(NB_VIEW, DATASET_LENGTH, NB_CLASS)
@@ -406,7 +421,7 @@ class Mumbo:
self.updateGeneralFs(DATASET_LENGTH, NB_CLASS, bestView)
self.updateGeneralCostMatrix(DATASET_LENGTH, NB_CLASS, CLASS_LABELS)
- # finalFs = computeFinalFs(DATASET_LENGTH, NB_CLASS, generalAlphas, predictions, bestViews, LABELS, NB_ITER)
+ # finalFs = computeFinalFs(DATASET_LENGTH, NB_CLASS, generalAlphas, predictions, bestViews, LABELS, NB_ITER)
def predict(self, DATASET, NB_CLASS=2):
DATASET_LENGTH = len(DATASET[0])
@@ -442,7 +457,7 @@ class Mumbo:
usedIndices = range(DATASET.get("Metadata").attrs["datasetLength"])
if usedIndices:
DATASET_LENGTH = len(usedIndices)
- predictedLabels = np.zeros((DATASET_LENGTH, self.nbIter))
+ predictedLabels = np.zeros((DATASET_LENGTH, self.maxIter))
votes = np.zeros((DATASET_LENGTH, NB_CLASS))
for iterIndex, (classifier, alpha, view) in enumerate(zip(self.bestClassifiers, self.alphas, self.bestViews)):
@@ -455,7 +470,7 @@ class Mumbo:
predictedLabels[usedExampleIndex, iterIndex] = np.argmax(votes[usedExampleIndex])
else:
predictedLabels = []
- for i in range(self.nbIter):
+ for i in range(self.maxIter):
predictedLabels.append([])
return np.transpose(predictedLabels)
diff --git a/Code/Multiview/Mumbo/__init__.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/__init__.py
similarity index 100%
rename from Code/Multiview/Mumbo/__init__.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/__init__.py
diff --git a/Code/Multiview/Mumbo/analyzeResults.py b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/analyzeResults.py
similarity index 99%
rename from Code/Multiview/Mumbo/analyzeResults.py
rename to Code/MonoMutliViewClassifiers/Multiview/Mumbo/analyzeResults.py
index 8d32066b5acc42666c21c70f4295eed8b6af4d4a..ebca53330f61e9c1e83cf350a72bdfed946b9972 100644
--- a/Code/Multiview/Mumbo/analyzeResults.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/Mumbo/analyzeResults.py
@@ -21,7 +21,7 @@ def plotAccuracyByIter(trainAccuracy, testAccuracy, validationAccuracy, NB_ITER,
figure = plt.figure()
ax1 = figure.add_subplot(111)
axes = figure.gca()
- axes.set_ylim([0,100])
+ axes.set_ylim([40,100])
titleString = ""
for view, classifierConfig in zip(features, classifierAnalysis):
titleString += "\n" + view + " : " + classifierConfig
diff --git a/Code/Multiview/Results/20160805-051412Results-Mumbo-DecisionTree:DecisionTree:DecisionTree:DecisionTree-Methyl-MiRNA-RNASEQ-Clinical-Methyl-MiRNA-RNASEQ-Clinical-learnRate2.0-nbIter10-Fake.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160805-051412Results-Mumbo-DecisionTree:DecisionTree:DecisionTree:DecisionTree-Methyl-MiRNA-RNASEQ-Clinical-Methyl-MiRNA-RNASEQ-Clinical-learnRate2.0-nbIter10-Fake.txt
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rename from Code/Multiview/Results/20160805-051412Results-Mumbo-DecisionTree:DecisionTree:DecisionTree:DecisionTree-Methyl-MiRNA-RNASEQ-Clinical-Methyl-MiRNA-RNASEQ-Clinical-learnRate2.0-nbIter10-Fake.txt
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160805-051412Results-Mumbo-DecisionTree:DecisionTree:DecisionTree:DecisionTree-Methyl-MiRNA-RNASEQ-Clinical-Methyl-MiRNA-RNASEQ-Clinical-learnRate2.0-nbIter10-Fake.txt
diff --git a/Code/Multiview/Results/20160805-051504Results-Mumbo-DecisionTree:DecisionTree:DecisionTree:DecisionTree-Methyl-MiRNA-RNASEQ-Clinical-Methyl-MiRNA-RNASEQ-Clinical-learnRate2.0-nbIter10-Fake-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160805-051504Results-Mumbo-DecisionTree:DecisionTree:DecisionTree:DecisionTree-Methyl-MiRNA-RNASEQ-Clinical-Methyl-MiRNA-RNASEQ-Clinical-learnRate2.0-nbIter10-Fake-accuracyByIteration.png
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diff --git a/Code/Multiview/Results/20160822-152017-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160822-152017-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160822-152017-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160822-152017-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160822-152034-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160822-152034-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160822-152034-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160822-152034-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160822-152113-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160822-152113-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160822-152113-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160822-152113-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-MultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-095233-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-095233-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-095233-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-095233-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-095734-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-095734-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-095734-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-095734-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-100003-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100003-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-100003-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100003-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-100209-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100209-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-100209-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100209-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-100355-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100355-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-100355-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100355-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-100549-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100549-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-100549-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100549-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-100728-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100728-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-100728-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-100728-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-101021-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101021-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-101021-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101021-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-101135-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101135-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-101135-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101135-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-101459-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101459-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-101459-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101459-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
diff --git a/Code/Multiview/Results/20160823-101527-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101527-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/20160823-101527-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/20160823-101527-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083255-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083255-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..442b823485ce2b64760c16e107ac9bb22a7044be
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083255-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,2 @@
+2016-08-24 08:32:55,450 INFO: Start: Read CSV Database Files for ModifiedMultiOmic
+2016-08-24 08:32:55,471 DEBUG: Start: Getting Methylation Data
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083315-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083315-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..0db771fc49da7eefd99a12fb35eed89bee226fbe
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083315-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,2 @@
+2016-08-24 08:33:15,026 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 08:33:15,027 INFO: Info: Labels used: No, Yes
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083427-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083427-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..ade5b1d09f18dffbc2de3ad96f12e5aefd03533c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-083427-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG.log
@@ -0,0 +1,10 @@
+2016-08-24 08:34:27,721 INFO: Start: Read CSV Database Files for MultiOmic
+2016-08-24 08:34:27,744 DEBUG: Start: Getting Methylation Data
+2016-08-24 08:34:40,551 DEBUG: Done: Getting Methylation Data
+2016-08-24 08:34:40,551 DEBUG: Start: Getting MiRNA Data
+2016-08-24 08:34:41,071 DEBUG: Done: Getting MiRNA Data
+2016-08-24 08:34:41,071 DEBUG: Start: Getting RNASeq Data
+2016-08-24 08:36:25,941 DEBUG: Done: Getting RNASeq Data
+2016-08-24 08:36:26,035 DEBUG: Start: Getting Clinical Data
+2016-08-24 08:36:26,594 DEBUG: Done: Getting Clinical Data
+2016-08-24 08:36:28,223 INFO: Info: Labels used: No, Yes
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084100-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084100-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..a816c4d772836bb3d4525da72af41a52802716b8
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084100-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,12 @@
+2016-08-24 08:41:00,873 INFO: Start: Read CSV Database Files for ModifiedMultiOmic
+2016-08-24 08:41:00,968 DEBUG: Start: Getting Methylation Data
+2016-08-24 08:41:13,912 DEBUG: Done: Getting Methylation Data
+2016-08-24 08:41:13,912 DEBUG: Start: Getting MiRNA Data
+2016-08-24 08:41:14,437 DEBUG: Done: Getting MiRNA Data
+2016-08-24 08:41:14,438 DEBUG: Start: Getting RNASeq Data
+2016-08-24 08:41:58,294 DEBUG: Done: Getting RNASeq Data
+2016-08-24 08:41:58,382 DEBUG: Start: Getting Clinical Data
+2016-08-24 08:41:58,478 DEBUG: Done: Getting Clinical Data
+2016-08-24 08:41:58,521 DEBUG: Start: Getting Modified RNASeq Data
+2016-08-24 08:42:49,046 DEBUG: Done: Getting Modified RNASeq Data
+2016-08-24 08:42:50,194 INFO: Info: Labels used: No, Yes
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084717-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084717-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..02a820c2cc336d69a134d9ff09531496cab240b4
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084717-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,21 @@
+2016-08-24 08:47:17,766 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 08:47:17,767 INFO: Info: Labels used: No, Yes
+2016-08-24 08:47:17,767 INFO: Info: Length of dataset:347
+2016-08-24 08:47:17,769 INFO: ### Main Programm for Multiview Classification
+2016-08-24 08:47:17,769 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 08:47:17,769 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 08:47:17,769 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 08:47:17,770 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 08:47:17,770 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 08:47:17,771 INFO: Done: Read Database Files
+2016-08-24 08:47:17,771 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 08:47:17,774 INFO: Done: Determine validation split
+2016-08-24 08:47:17,774 INFO: Start: Determine 2 folds
+2016-08-24 08:47:17,783 INFO: Info: Length of Learning Sets: 122
+2016-08-24 08:47:17,783 INFO: Info: Length of Testing Sets: 122
+2016-08-24 08:47:17,783 INFO: Info: Length of Validation Set: 103
+2016-08-24 08:47:17,783 INFO: Done: Determine folds
+2016-08-24 08:47:17,783 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 08:47:17,784 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 08:48:32,759 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 08:48:32,759 INFO: Start: Fold number 1
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084943-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084943-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..a96b7a7ef59c7050952add93a0ca4cccbae871ab
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-084943-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,97 @@
+2016-08-24 08:49:43,519 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 08:49:43,519 INFO: Info: Labels used: No, Yes
+2016-08-24 08:49:43,520 INFO: Info: Length of dataset:347
+2016-08-24 08:49:43,521 INFO: ### Main Programm for Multiview Classification
+2016-08-24 08:49:43,521 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 08:49:43,522 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 08:49:43,522 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 08:49:43,523 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 08:49:43,523 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 08:49:43,523 INFO: Done: Read Database Files
+2016-08-24 08:49:43,523 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 08:49:43,527 INFO: Done: Determine validation split
+2016-08-24 08:49:43,527 INFO: Start: Determine 2 folds
+2016-08-24 08:49:43,537 INFO: Info: Length of Learning Sets: 122
+2016-08-24 08:49:43,537 INFO: Info: Length of Testing Sets: 122
+2016-08-24 08:49:43,537 INFO: Info: Length of Validation Set: 103
+2016-08-24 08:49:43,537 INFO: Done: Determine folds
+2016-08-24 08:49:43,537 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 08:49:43,537 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 08:49:43,537 DEBUG: Start: Gridsearch for DecisionTree
+2016-08-24 08:49:51,018 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:49:51,018 DEBUG: Start: Gridsearch for DecisionTree
+2016-08-24 08:49:52,921 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:49:52,921 DEBUG: Start: Gridsearch for DecisionTree
+2016-08-24 08:50:09,522 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:50:09,522 DEBUG: Start: Gridsearch for DecisionTree
+2016-08-24 08:50:11,247 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:50:11,247 DEBUG: Start: Gridsearch for DecisionTree
+2016-08-24 08:50:51,870 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:50:51,871 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 08:50:51,871 INFO: Start: Fold number 1
+2016-08-24 08:50:53,455 DEBUG: Start: Iteration 1
+2016-08-24 08:50:53,476 DEBUG: View 0 : 0.605263157895
+2016-08-24 08:50:53,484 DEBUG: View 1 : 0.605263157895
+2016-08-24 08:50:53,520 DEBUG: View 2 : 0.611842105263
+2016-08-24 08:50:53,528 DEBUG: View 3 : 0.493421052632
+2016-08-24 08:50:53,568 DEBUG: Best view : RANSeq_
+2016-08-24 08:50:53,652 DEBUG: Start: Iteration 2
+2016-08-24 08:50:53,669 DEBUG: View 0 : 0.605263157895
+2016-08-24 08:50:53,677 DEBUG: View 1 : 0.605263157895
+2016-08-24 08:50:53,713 DEBUG: View 2 : 0.394736842105
+2016-08-24 08:50:53,720 DEBUG: View 3 : 0.532894736842
+2016-08-24 08:50:53,763 DEBUG: Best view : Methyl_
+2016-08-24 08:50:53,908 DEBUG: Start: Iteration 3
+2016-08-24 08:50:53,924 DEBUG: View 0 : 0.565789473684
+2016-08-24 08:50:53,931 DEBUG: View 1 : 0.710526315789
+2016-08-24 08:50:53,966 DEBUG: View 2 : 0.407894736842
+2016-08-24 08:50:53,974 DEBUG: View 3 : 0.460526315789
+2016-08-24 08:50:54,024 DEBUG: Best view : MiRNA__
+2016-08-24 08:50:54,225 DEBUG: Start: Iteration 4
+2016-08-24 08:50:54,241 DEBUG: View 0 : 0.407894736842
+2016-08-24 08:50:54,249 DEBUG: View 1 : 0.427631578947
+2016-08-24 08:50:54,285 DEBUG: View 2 : 0.598684210526
+2016-08-24 08:50:54,292 DEBUG: View 3 : 0.519736842105
+2016-08-24 08:50:54,345 DEBUG: Best view : RANSeq_
+2016-08-24 08:50:54,614 DEBUG: Start: Iteration 5
+2016-08-24 08:50:54,630 DEBUG: View 0 : 0.565789473684
+2016-08-24 08:50:54,638 DEBUG: View 1 : 0.552631578947
+2016-08-24 08:50:54,673 DEBUG: View 2 : 0.480263157895
+2016-08-24 08:50:54,681 DEBUG: View 3 : 0.526315789474
+2016-08-24 08:50:54,736 DEBUG: Best view : MiRNA__
+2016-08-24 08:50:55,067 DEBUG: Start: Iteration 6
+2016-08-24 08:50:55,083 DEBUG: View 0 : 0.585526315789
+2016-08-24 08:50:55,090 DEBUG: View 1 : 0.381578947368
+2016-08-24 08:50:55,127 DEBUG: View 2 : 0.453947368421
+2016-08-24 08:50:55,134 DEBUG: View 3 : 0.467105263158
+2016-08-24 08:50:55,193 DEBUG: Best view : Methyl_
+2016-08-24 08:50:55,584 DEBUG: Start: Iteration 7
+2016-08-24 08:50:55,601 DEBUG: View 0 : 0.822368421053
+2016-08-24 08:50:55,609 DEBUG: View 1 : 0.651315789474
+2016-08-24 08:50:55,645 DEBUG: View 2 : 0.480263157895
+2016-08-24 08:50:55,653 DEBUG: View 3 : 0.375
+2016-08-24 08:50:55,712 DEBUG: Best view : Methyl_
+2016-08-24 08:50:56,161 DEBUG: Start: Iteration 8
+2016-08-24 08:50:56,178 DEBUG: View 0 : 0.638157894737
+2016-08-24 08:50:56,185 DEBUG: View 1 : 0.578947368421
+2016-08-24 08:50:56,221 DEBUG: View 2 : 0.631578947368
+2016-08-24 08:50:56,228 DEBUG: View 3 : 0.407894736842
+2016-08-24 08:50:56,290 DEBUG: Best view : Methyl_
+2016-08-24 08:50:56,793 DEBUG: Start: Iteration 9
+2016-08-24 08:50:56,809 DEBUG: View 0 : 0.532894736842
+2016-08-24 08:50:56,816 DEBUG: View 1 : 0.539473684211
+2016-08-24 08:50:56,852 DEBUG: View 2 : 0.532894736842
+2016-08-24 08:50:56,860 DEBUG: View 3 : 0.585526315789
+2016-08-24 08:50:56,923 DEBUG: Best view : Clinic_
+2016-08-24 08:50:57,481 DEBUG: Start: Iteration 10
+2016-08-24 08:50:57,497 DEBUG: View 0 : 0.618421052632
+2016-08-24 08:50:57,505 DEBUG: View 1 : 0.361842105263
+2016-08-24 08:50:57,541 DEBUG: View 2 : 0.394736842105
+2016-08-24 08:50:57,548 DEBUG: View 3 : 0.664473684211
+2016-08-24 08:50:57,614 DEBUG: Best view : Clinic_
+2016-08-24 08:50:58,229 DEBUG: Start: Iteration 11
+2016-08-24 08:50:58,244 DEBUG: View 0 : 0.565789473684
+2016-08-24 08:50:58,252 DEBUG: View 1 : 0.421052631579
+2016-08-24 08:50:58,287 DEBUG: View 2 : 0.539473684211
+2016-08-24 08:50:58,295 DEBUG: View 3 : 0.493421052632
+2016-08-24 08:50:58,363 DEBUG: Best view : Methyl_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085300-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085300-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..4b32381dc0c1d10aa5378d41a4fe63fa2b29129e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085300-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,24 @@
+2016-08-24 08:53:00,304 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 08:53:00,305 INFO: Info: Labels used: No, Yes
+2016-08-24 08:53:00,306 INFO: Info: Length of dataset:347
+2016-08-24 08:53:00,309 INFO: ### Main Programm for Multiview Classification
+2016-08-24 08:53:00,309 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 08:53:00,311 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 08:53:00,312 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 08:53:00,313 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 08:53:00,314 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 08:53:00,314 INFO: Done: Read Database Files
+2016-08-24 08:53:00,314 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 08:53:00,320 INFO: Done: Determine validation split
+2016-08-24 08:53:00,320 INFO: Start: Determine 2 folds
+2016-08-24 08:53:00,330 INFO: Info: Length of Learning Sets: 122
+2016-08-24 08:53:00,330 INFO: Info: Length of Testing Sets: 122
+2016-08-24 08:53:00,330 INFO: Info: Length of Validation Set: 103
+2016-08-24 08:53:00,331 INFO: Done: Determine folds
+2016-08-24 08:53:00,331 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 08:53:00,331 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 08:53:00,331 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 08:53:07,603 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:53:07,604 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 08:53:09,500 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:53:09,500 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085340-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085340-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..38b211e35c099fc1b340a169cf5e3f9bb8bd9ed0
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085340-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,97 @@
+2016-08-24 08:53:40,067 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 08:53:40,068 INFO: Info: Labels used: No, Yes
+2016-08-24 08:53:40,068 INFO: Info: Length of dataset:347
+2016-08-24 08:53:40,069 INFO: ### Main Programm for Multiview Classification
+2016-08-24 08:53:40,069 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 08:53:40,070 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 08:53:40,070 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 08:53:40,071 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 08:53:40,071 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 08:53:40,071 INFO: Done: Read Database Files
+2016-08-24 08:53:40,071 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 08:53:40,075 INFO: Done: Determine validation split
+2016-08-24 08:53:40,075 INFO: Start: Determine 2 folds
+2016-08-24 08:53:40,085 INFO: Info: Length of Learning Sets: 122
+2016-08-24 08:53:40,085 INFO: Info: Length of Testing Sets: 122
+2016-08-24 08:53:40,085 INFO: Info: Length of Validation Set: 103
+2016-08-24 08:53:40,085 INFO: Done: Determine folds
+2016-08-24 08:53:40,085 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 08:53:40,085 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 08:53:40,086 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 08:53:47,504 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:53:47,504 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 08:53:49,404 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:53:49,405 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 08:54:06,005 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:54:06,006 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 08:54:07,742 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:54:07,742 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 08:54:44,843 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:54:44,843 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 08:54:44,844 INFO: Start: Fold number 1
+2016-08-24 08:54:46,449 DEBUG: Start: Iteration 1
+2016-08-24 08:54:46,465 DEBUG: View 0 : 0.631901840491
+2016-08-24 08:54:46,473 DEBUG: View 1 : 0.638036809816
+2016-08-24 08:54:46,510 DEBUG: View 2 : 0.441717791411
+2016-08-24 08:54:46,518 DEBUG: View 3 : 0.631901840491
+2016-08-24 08:54:46,561 DEBUG: Best view : Methyl_
+2016-08-24 08:54:46,662 DEBUG: Start: Iteration 2
+2016-08-24 08:54:46,680 DEBUG: View 0 : 0.503067484663
+2016-08-24 08:54:46,688 DEBUG: View 1 : 0.466257668712
+2016-08-24 08:54:46,726 DEBUG: View 2 : 0.478527607362
+2016-08-24 08:54:46,734 DEBUG: View 3 : 0.441717791411
+2016-08-24 08:54:46,781 DEBUG: Best view : Methyl_
+2016-08-24 08:54:46,945 DEBUG: Start: Iteration 3
+2016-08-24 08:54:46,962 DEBUG: View 0 : 0.361963190184
+2016-08-24 08:54:46,970 DEBUG: View 1 : 0.613496932515
+2016-08-24 08:54:47,008 DEBUG: View 2 : 0.411042944785
+2016-08-24 08:54:47,016 DEBUG: View 3 : 0.656441717791
+2016-08-24 08:54:47,071 DEBUG: Best view : Clinic_
+2016-08-24 08:54:47,297 DEBUG: Start: Iteration 4
+2016-08-24 08:54:47,314 DEBUG: View 0 : 0.435582822086
+2016-08-24 08:54:47,322 DEBUG: View 1 : 0.509202453988
+2016-08-24 08:54:47,360 DEBUG: View 2 : 0.38036809816
+2016-08-24 08:54:47,368 DEBUG: View 3 : 0.631901840491
+2016-08-24 08:54:47,426 DEBUG: Best view : Clinic_
+2016-08-24 08:54:47,709 DEBUG: Start: Iteration 5
+2016-08-24 08:54:47,726 DEBUG: View 0 : 0.638036809816
+2016-08-24 08:54:47,734 DEBUG: View 1 : 0.564417177914
+2016-08-24 08:54:47,772 DEBUG: View 2 : 0.39263803681
+2016-08-24 08:54:47,780 DEBUG: View 3 : 0.546012269939
+2016-08-24 08:54:47,841 DEBUG: Best view : Methyl_
+2016-08-24 08:54:48,187 DEBUG: Start: Iteration 6
+2016-08-24 08:54:48,204 DEBUG: View 0 : 0.509202453988
+2016-08-24 08:54:48,211 DEBUG: View 1 : 0.638036809816
+2016-08-24 08:54:48,250 DEBUG: View 2 : 0.564417177914
+2016-08-24 08:54:48,258 DEBUG: View 3 : 0.558282208589
+2016-08-24 08:54:48,320 DEBUG: Best view : MiRNA__
+2016-08-24 08:54:48,727 DEBUG: Start: Iteration 7
+2016-08-24 08:54:48,744 DEBUG: View 0 : 0.564417177914
+2016-08-24 08:54:48,752 DEBUG: View 1 : 0.533742331288
+2016-08-24 08:54:48,791 DEBUG: View 2 : 0.509202453988
+2016-08-24 08:54:48,799 DEBUG: View 3 : 0.466257668712
+2016-08-24 08:54:48,863 DEBUG: Best view : Methyl_
+2016-08-24 08:54:49,333 DEBUG: Start: Iteration 8
+2016-08-24 08:54:49,350 DEBUG: View 0 : 0.423312883436
+2016-08-24 08:54:49,358 DEBUG: View 1 : 0.39263803681
+2016-08-24 08:54:49,396 DEBUG: View 2 : 0.40490797546
+2016-08-24 08:54:49,404 DEBUG: View 3 : 0.546012269939
+2016-08-24 08:54:49,471 DEBUG: Best view : Clinic_
+2016-08-24 08:54:50,001 DEBUG: Start: Iteration 9
+2016-08-24 08:54:50,018 DEBUG: View 0 : 0.478527607362
+2016-08-24 08:54:50,025 DEBUG: View 1 : 0.368098159509
+2016-08-24 08:54:50,063 DEBUG: View 2 : 0.631901840491
+2016-08-24 08:54:50,071 DEBUG: View 3 : 0.539877300613
+2016-08-24 08:54:50,141 DEBUG: Best view : RANSeq_
+2016-08-24 08:54:50,745 DEBUG: Start: Iteration 10
+2016-08-24 08:54:50,762 DEBUG: View 0 : 0.576687116564
+2016-08-24 08:54:50,770 DEBUG: View 1 : 0.496932515337
+2016-08-24 08:54:50,808 DEBUG: View 2 : 0.613496932515
+2016-08-24 08:54:50,816 DEBUG: View 3 : 0.374233128834
+2016-08-24 08:54:50,888 DEBUG: Best view : RANSeq_
+2016-08-24 08:54:51,566 DEBUG: Start: Iteration 11
+2016-08-24 08:54:51,583 DEBUG: View 0 : 0.472392638037
+2016-08-24 08:54:51,591 DEBUG: View 1 : 0.435582822086
+2016-08-24 08:54:51,629 DEBUG: View 2 : 0.478527607362
+2016-08-24 08:54:51,637 DEBUG: View 3 : 0.576687116564
+2016-08-24 08:54:51,711 DEBUG: Best view : Clinic_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085528-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085528-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..85f1830f76c6e72e0f194afef0d44aa915a055a9
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-085528-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,98 @@
+2016-08-24 08:55:28,014 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 08:55:28,015 INFO: Info: Labels used: No, Yes
+2016-08-24 08:55:28,015 INFO: Info: Length of dataset:347
+2016-08-24 08:55:28,016 INFO: ### Main Programm for Multiview Classification
+2016-08-24 08:55:28,017 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 08:55:28,017 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 08:55:28,017 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 08:55:28,018 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 08:55:28,019 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 08:55:28,019 INFO: Done: Read Database Files
+2016-08-24 08:55:28,019 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 08:55:28,025 INFO: Done: Determine validation split
+2016-08-24 08:55:28,025 INFO: Start: Determine 2 folds
+2016-08-24 08:55:28,039 INFO: Info: Length of Learning Sets: 122
+2016-08-24 08:55:28,040 INFO: Info: Length of Testing Sets: 122
+2016-08-24 08:55:28,040 INFO: Info: Length of Validation Set: 103
+2016-08-24 08:55:28,040 INFO: Done: Determine folds
+2016-08-24 08:55:28,040 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 08:55:28,040 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 08:55:28,040 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 08:55:35,427 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:55:35,427 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 08:55:37,400 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:55:37,401 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 08:55:55,603 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:55:55,604 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 08:55:57,380 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:55:57,381 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 08:56:35,467 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 08:56:35,467 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 08:56:35,467 INFO: Start: Fold number 1
+2016-08-24 08:56:37,036 DEBUG: Start: Iteration 1
+2016-08-24 08:56:37,052 DEBUG: View 0 : 0.37037037037
+2016-08-24 08:56:37,060 DEBUG: View 1 : 0.62962962963
+2016-08-24 08:56:37,089 DEBUG: View 2 : 0.37037037037
+2016-08-24 08:56:37,096 DEBUG: View 3 : 0.530864197531
+2016-08-24 08:56:37,139 DEBUG: Best view : Methyl_
+2016-08-24 08:56:37,218 DEBUG: Start: Iteration 2
+2016-08-24 08:56:37,235 DEBUG: View 0 : 0.481481481481
+2016-08-24 08:56:37,242 DEBUG: View 1 : 0.41975308642
+2016-08-24 08:56:37,279 DEBUG: View 2 : 0.481481481481
+2016-08-24 08:56:37,287 DEBUG: View 3 : 0.530864197531
+2016-08-24 08:56:37,339 DEBUG: Best view : Clinic_
+2016-08-24 08:56:37,477 DEBUG: Start: Iteration 3
+2016-08-24 08:56:37,494 DEBUG: View 0 : 0.438271604938
+2016-08-24 08:56:37,502 DEBUG: View 1 : 0.407407407407
+2016-08-24 08:56:37,539 DEBUG: View 2 : 0.382716049383
+2016-08-24 08:56:37,547 DEBUG: View 3 : 0.376543209877
+2016-08-24 08:56:37,547 WARNING: All bad for iteration 2
+2016-08-24 08:56:37,602 DEBUG: Best view : Methyl_
+2016-08-24 08:56:37,803 DEBUG: Start: Iteration 4
+2016-08-24 08:56:37,819 DEBUG: View 0 : 0.604938271605
+2016-08-24 08:56:37,827 DEBUG: View 1 : 0.271604938272
+2016-08-24 08:56:37,864 DEBUG: View 2 : 0.469135802469
+2016-08-24 08:56:37,872 DEBUG: View 3 : 0.487654320988
+2016-08-24 08:56:37,929 DEBUG: Best view : Methyl_
+2016-08-24 08:56:38,194 DEBUG: Start: Iteration 5
+2016-08-24 08:56:38,211 DEBUG: View 0 : 0.395061728395
+2016-08-24 08:56:38,219 DEBUG: View 1 : 0.413580246914
+2016-08-24 08:56:38,256 DEBUG: View 2 : 0.481481481481
+2016-08-24 08:56:38,264 DEBUG: View 3 : 0.506172839506
+2016-08-24 08:56:38,323 DEBUG: Best view : Clinic_
+2016-08-24 08:56:38,648 DEBUG: Start: Iteration 6
+2016-08-24 08:56:38,665 DEBUG: View 0 : 0.543209876543
+2016-08-24 08:56:38,672 DEBUG: View 1 : 0.425925925926
+2016-08-24 08:56:38,709 DEBUG: View 2 : 0.376543209877
+2016-08-24 08:56:38,717 DEBUG: View 3 : 0.586419753086
+2016-08-24 08:56:38,780 DEBUG: Best view : Clinic_
+2016-08-24 08:56:39,164 DEBUG: Start: Iteration 7
+2016-08-24 08:56:39,180 DEBUG: View 0 : 0.561728395062
+2016-08-24 08:56:39,188 DEBUG: View 1 : 0.5
+2016-08-24 08:56:39,225 DEBUG: View 2 : 0.537037037037
+2016-08-24 08:56:39,233 DEBUG: View 3 : 0.567901234568
+2016-08-24 08:56:39,298 DEBUG: Best view : Methyl_
+2016-08-24 08:56:39,744 DEBUG: Start: Iteration 8
+2016-08-24 08:56:39,761 DEBUG: View 0 : 0.592592592593
+2016-08-24 08:56:39,769 DEBUG: View 1 : 0.438271604938
+2016-08-24 08:56:39,806 DEBUG: View 2 : 0.456790123457
+2016-08-24 08:56:39,813 DEBUG: View 3 : 0.530864197531
+2016-08-24 08:56:39,880 DEBUG: Best view : Methyl_
+2016-08-24 08:56:40,391 DEBUG: Start: Iteration 9
+2016-08-24 08:56:40,408 DEBUG: View 0 : 0.561728395062
+2016-08-24 08:56:40,416 DEBUG: View 1 : 0.413580246914
+2016-08-24 08:56:40,453 DEBUG: View 2 : 0.617283950617
+2016-08-24 08:56:40,461 DEBUG: View 3 : 0.512345679012
+2016-08-24 08:56:40,530 DEBUG: Best view : RANSeq_
+2016-08-24 08:56:41,117 DEBUG: Start: Iteration 10
+2016-08-24 08:56:41,133 DEBUG: View 0 : 0.648148148148
+2016-08-24 08:56:41,141 DEBUG: View 1 : 0.456790123457
+2016-08-24 08:56:41,178 DEBUG: View 2 : 0.407407407407
+2016-08-24 08:56:41,186 DEBUG: View 3 : 0.66049382716
+2016-08-24 08:56:41,257 DEBUG: Best view : Methyl_
+2016-08-24 08:56:41,906 DEBUG: Start: Iteration 11
+2016-08-24 08:56:41,923 DEBUG: View 0 : 0.401234567901
+2016-08-24 08:56:41,931 DEBUG: View 1 : 0.586419753086
+2016-08-24 08:56:41,968 DEBUG: View 2 : 0.382716049383
+2016-08-24 08:56:41,975 DEBUG: View 3 : 0.493827160494
+2016-08-24 08:56:42,049 DEBUG: Best view : MiRNA__
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-090120-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-090120-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..d966042b8c769ee3c568fa17c888a780b691af94
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-090120-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,97 @@
+2016-08-24 09:01:20,823 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:01:20,823 INFO: Info: Labels used: No, Yes
+2016-08-24 09:01:20,823 INFO: Info: Length of dataset:347
+2016-08-24 09:01:20,825 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:01:20,825 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:01:20,825 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:01:20,826 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:01:20,826 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:01:20,827 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:01:20,827 INFO: Done: Read Database Files
+2016-08-24 09:01:20,827 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:01:20,830 INFO: Done: Determine validation split
+2016-08-24 09:01:20,830 INFO: Start: Determine 2 folds
+2016-08-24 09:01:20,838 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:01:20,838 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:01:20,838 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:01:20,838 INFO: Done: Determine folds
+2016-08-24 09:01:20,839 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:01:20,839 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:01:20,839 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:01:28,173 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:01:28,173 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:01:30,085 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:01:30,086 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:01:46,691 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:01:46,691 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:01:48,441 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:01:48,441 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:02:44,634 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:02:44,634 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:02:44,634 INFO: Start: Fold number 1
+2016-08-24 09:02:46,206 DEBUG: Start: Iteration 1
+2016-08-24 09:02:46,269 DEBUG: View 0 : 0.37037037037
+2016-08-24 09:02:46,303 DEBUG: View 1 : 0.623456790123
+2016-08-24 09:02:46,497 DEBUG: View 2 : 0.648148148148
+2016-08-24 09:02:46,505 DEBUG: View 3 : 0.62962962963
+2016-08-24 09:02:46,552 DEBUG: Best view : Methyl_
+2016-08-24 09:02:46,634 DEBUG: Start: Iteration 2
+2016-08-24 09:02:46,652 DEBUG: View 0 : 0.438271604938
+2016-08-24 09:02:46,660 DEBUG: View 1 : 0.493827160494
+2016-08-24 09:02:46,699 DEBUG: View 2 : 0.549382716049
+2016-08-24 09:02:46,707 DEBUG: View 3 : 0.518518518519
+2016-08-24 09:02:46,760 DEBUG: Best view : RANSeq_
+2016-08-24 09:02:46,915 DEBUG: Start: Iteration 3
+2016-08-24 09:02:46,932 DEBUG: View 0 : 0.543209876543
+2016-08-24 09:02:46,940 DEBUG: View 1 : 0.425925925926
+2016-08-24 09:02:46,978 DEBUG: View 2 : 0.518518518519
+2016-08-24 09:02:46,985 DEBUG: View 3 : 0.648148148148
+2016-08-24 09:02:47,040 DEBUG: Best view : Clinic_
+2016-08-24 09:02:47,253 DEBUG: Start: Iteration 4
+2016-08-24 09:02:47,270 DEBUG: View 0 : 0.432098765432
+2016-08-24 09:02:47,278 DEBUG: View 1 : 0.623456790123
+2016-08-24 09:02:47,316 DEBUG: View 2 : 0.456790123457
+2016-08-24 09:02:47,324 DEBUG: View 3 : 0.537037037037
+2016-08-24 09:02:47,381 DEBUG: Best view : MiRNA__
+2016-08-24 09:02:47,652 DEBUG: Start: Iteration 5
+2016-08-24 09:02:47,669 DEBUG: View 0 : 0.395061728395
+2016-08-24 09:02:47,677 DEBUG: View 1 : 0.561728395062
+2016-08-24 09:02:47,715 DEBUG: View 2 : 0.524691358025
+2016-08-24 09:02:47,723 DEBUG: View 3 : 0.413580246914
+2016-08-24 09:02:47,781 DEBUG: Best view : MiRNA__
+2016-08-24 09:02:48,113 DEBUG: Start: Iteration 6
+2016-08-24 09:02:48,130 DEBUG: View 0 : 0.716049382716
+2016-08-24 09:02:48,138 DEBUG: View 1 : 0.351851851852
+2016-08-24 09:02:48,176 DEBUG: View 2 : 0.549382716049
+2016-08-24 09:02:48,183 DEBUG: View 3 : 0.530864197531
+2016-08-24 09:02:48,245 DEBUG: Best view : Methyl_
+2016-08-24 09:02:48,639 DEBUG: Start: Iteration 7
+2016-08-24 09:02:48,656 DEBUG: View 0 : 0.598765432099
+2016-08-24 09:02:48,664 DEBUG: View 1 : 0.524691358025
+2016-08-24 09:02:48,701 DEBUG: View 2 : 0.524691358025
+2016-08-24 09:02:48,709 DEBUG: View 3 : 0.382716049383
+2016-08-24 09:02:48,773 DEBUG: Best view : Methyl_
+2016-08-24 09:02:49,242 DEBUG: Start: Iteration 8
+2016-08-24 09:02:49,262 DEBUG: View 0 : 0.33950617284
+2016-08-24 09:02:49,272 DEBUG: View 1 : 0.617283950617
+2016-08-24 09:02:49,315 DEBUG: View 2 : 0.5
+2016-08-24 09:02:49,325 DEBUG: View 3 : 0.574074074074
+2016-08-24 09:02:49,401 DEBUG: Best view : MiRNA__
+2016-08-24 09:02:49,959 DEBUG: Start: Iteration 9
+2016-08-24 09:02:49,975 DEBUG: View 0 : 0.512345679012
+2016-08-24 09:02:49,984 DEBUG: View 1 : 0.537037037037
+2016-08-24 09:02:50,021 DEBUG: View 2 : 0.438271604938
+2016-08-24 09:02:50,029 DEBUG: View 3 : 0.604938271605
+2016-08-24 09:02:50,097 DEBUG: Best view : Clinic_
+2016-08-24 09:02:50,670 DEBUG: Start: Iteration 10
+2016-08-24 09:02:50,687 DEBUG: View 0 : 0.401234567901
+2016-08-24 09:02:50,695 DEBUG: View 1 : 0.635802469136
+2016-08-24 09:02:50,733 DEBUG: View 2 : 0.518518518519
+2016-08-24 09:02:50,740 DEBUG: View 3 : 0.543209876543
+2016-08-24 09:02:50,811 DEBUG: Best view : MiRNA__
+2016-08-24 09:02:51,445 DEBUG: Start: Iteration 11
+2016-08-24 09:02:51,462 DEBUG: View 0 : 0.592592592593
+2016-08-24 09:02:51,470 DEBUG: View 1 : 0.537037037037
+2016-08-24 09:02:51,508 DEBUG: View 2 : 0.388888888889
+2016-08-24 09:02:51,516 DEBUG: View 3 : 0.450617283951
+2016-08-24 09:02:51,589 DEBUG: Best view : Methyl_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-090956-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-090956-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..ca2735947d563b15d49a2c78cc76f9886ddc8ced
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-090956-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,14246 @@
+2016-08-24 09:09:56,962 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:09:56,963 INFO: Info: Labels used: No, Yes
+2016-08-24 09:09:56,963 INFO: Info: Length of dataset:347
+2016-08-24 09:09:56,973 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:09:56,973 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:09:56,973 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:09:56,974 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:09:56,974 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:09:56,975 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:09:56,975 INFO: Done: Read Database Files
+2016-08-24 09:09:56,975 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:09:56,978 INFO: Done: Determine validation split
+2016-08-24 09:09:56,978 INFO: Start: Determine 2 folds
+2016-08-24 09:09:56,987 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:09:56,987 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:09:56,988 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:09:56,988 INFO: Done: Determine folds
+2016-08-24 09:09:56,988 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:09:56,988 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:09:56,988 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:10:04,379 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:10:04,380 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:10:06,314 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:10:06,315 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:10:23,238 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:10:23,238 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:10:25,001 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:10:25,002 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:11:02,594 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:11:02,594 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:11:02,594 INFO: Start: Fold number 1
+2016-08-24 09:11:04,137 DEBUG: Start: Iteration 1
+2016-08-24 09:11:04,153 DEBUG: View 0 : 0.622641509434
+2016-08-24 09:11:04,161 DEBUG: View 1 : 0.339622641509
+2016-08-24 09:11:04,189 DEBUG: View 2 : 0.622641509434
+2016-08-24 09:11:04,197 DEBUG: View 3 : 0.377358490566
+2016-08-24 09:11:04,239 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:04,311 DEBUG: Start: Iteration 2
+2016-08-24 09:11:04,328 DEBUG: View 0 : 0.534591194969
+2016-08-24 09:11:04,336 DEBUG: View 1 : 0.522012578616
+2016-08-24 09:11:04,373 DEBUG: View 2 : 0.540880503145
+2016-08-24 09:11:04,381 DEBUG: View 3 : 0.477987421384
+2016-08-24 09:11:04,426 DEBUG: Best view : RANSeq_
+2016-08-24 09:11:04,573 DEBUG: Start: Iteration 3
+2016-08-24 09:11:04,590 DEBUG: View 0 : 0.603773584906
+2016-08-24 09:11:04,598 DEBUG: View 1 : 0.566037735849
+2016-08-24 09:11:04,636 DEBUG: View 2 : 0.553459119497
+2016-08-24 09:11:04,643 DEBUG: View 3 : 0.62893081761
+2016-08-24 09:11:04,696 DEBUG: Best view : Clinic_
+2016-08-24 09:11:04,902 DEBUG: Start: Iteration 4
+2016-08-24 09:11:04,918 DEBUG: View 0 : 0.496855345912
+2016-08-24 09:11:04,926 DEBUG: View 1 : 0.51572327044
+2016-08-24 09:11:04,963 DEBUG: View 2 : 0.62893081761
+2016-08-24 09:11:04,970 DEBUG: View 3 : 0.421383647799
+2016-08-24 09:11:05,025 DEBUG: Best view : RANSeq_
+2016-08-24 09:11:05,308 DEBUG: Start: Iteration 5
+2016-08-24 09:11:05,324 DEBUG: View 0 : 0.477987421384
+2016-08-24 09:11:05,332 DEBUG: View 1 : 0.685534591195
+2016-08-24 09:11:05,369 DEBUG: View 2 : 0.452830188679
+2016-08-24 09:11:05,377 DEBUG: View 3 : 0.584905660377
+2016-08-24 09:11:05,434 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:05,769 DEBUG: Start: Iteration 6
+2016-08-24 09:11:05,786 DEBUG: View 0 : 0.433962264151
+2016-08-24 09:11:05,793 DEBUG: View 1 : 0.333333333333
+2016-08-24 09:11:05,830 DEBUG: View 2 : 0.396226415094
+2016-08-24 09:11:05,838 DEBUG: View 3 : 0.616352201258
+2016-08-24 09:11:05,899 DEBUG: Best view : Clinic_
+2016-08-24 09:11:06,295 DEBUG: Start: Iteration 7
+2016-08-24 09:11:06,311 DEBUG: View 0 : 0.509433962264
+2016-08-24 09:11:06,319 DEBUG: View 1 : 0.295597484277
+2016-08-24 09:11:06,356 DEBUG: View 2 : 0.471698113208
+2016-08-24 09:11:06,364 DEBUG: View 3 : 0.427672955975
+2016-08-24 09:11:06,426 DEBUG: Best view : Methyl_
+2016-08-24 09:11:06,881 DEBUG: Start: Iteration 8
+2016-08-24 09:11:06,897 DEBUG: View 0 : 0.452830188679
+2016-08-24 09:11:06,905 DEBUG: View 1 : 0.295597484277
+2016-08-24 09:11:06,942 DEBUG: View 2 : 0.440251572327
+2016-08-24 09:11:06,950 DEBUG: View 3 : 0.62893081761
+2016-08-24 09:11:07,016 DEBUG: Best view : Clinic_
+2016-08-24 09:11:07,528 DEBUG: Start: Iteration 9
+2016-08-24 09:11:07,544 DEBUG: View 0 : 0.522012578616
+2016-08-24 09:11:07,552 DEBUG: View 1 : 0.754716981132
+2016-08-24 09:11:07,589 DEBUG: View 2 : 0.534591194969
+2016-08-24 09:11:07,597 DEBUG: View 3 : 0.396226415094
+2016-08-24 09:11:07,664 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:08,239 DEBUG: Start: Iteration 10
+2016-08-24 09:11:08,256 DEBUG: View 0 : 0.48427672956
+2016-08-24 09:11:08,263 DEBUG: View 1 : 0.654088050314
+2016-08-24 09:11:08,301 DEBUG: View 2 : 0.610062893082
+2016-08-24 09:11:08,310 DEBUG: View 3 : 0.572327044025
+2016-08-24 09:11:08,380 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:09,007 DEBUG: Start: Iteration 11
+2016-08-24 09:11:09,024 DEBUG: View 0 : 0.51572327044
+2016-08-24 09:11:09,032 DEBUG: View 1 : 0.559748427673
+2016-08-24 09:11:09,069 DEBUG: View 2 : 0.534591194969
+2016-08-24 09:11:09,077 DEBUG: View 3 : 0.389937106918
+2016-08-24 09:11:09,148 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:09,842 DEBUG: Start: Iteration 12
+2016-08-24 09:11:09,873 DEBUG: View 0 : 0.503144654088
+2016-08-24 09:11:09,881 DEBUG: View 1 : 0.748427672956
+2016-08-24 09:11:09,918 DEBUG: View 2 : 0.540880503145
+2016-08-24 09:11:09,926 DEBUG: View 3 : 0.503144654088
+2016-08-24 09:11:09,999 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:10,742 INFO: Start: Classification
+2016-08-24 09:11:12,499 INFO: Done: Fold number 1
+2016-08-24 09:11:12,499 INFO: Start: Fold number 2
+2016-08-24 09:11:14,013 DEBUG: Start: Iteration 1
+2016-08-24 09:11:14,027 DEBUG: View 0 : 0.617834394904
+2016-08-24 09:11:14,035 DEBUG: View 1 : 0.382165605096
+2016-08-24 09:11:14,062 DEBUG: View 2 : 0.617834394904
+2016-08-24 09:11:14,070 DEBUG: View 3 : 0.528662420382
+2016-08-24 09:11:14,108 DEBUG: Best view : Methyl_
+2016-08-24 09:11:14,183 DEBUG: Start: Iteration 2
+2016-08-24 09:11:14,199 DEBUG: View 0 : 0.496815286624
+2016-08-24 09:11:14,207 DEBUG: View 1 : 0.420382165605
+2016-08-24 09:11:14,243 DEBUG: View 2 : 0.426751592357
+2016-08-24 09:11:14,250 DEBUG: View 3 : 0.426751592357
+2016-08-24 09:11:14,250 WARNING: All bad for iteration 1
+2016-08-24 09:11:14,299 DEBUG: Best view : Methyl_
+2016-08-24 09:11:14,436 DEBUG: Start: Iteration 3
+2016-08-24 09:11:14,452 DEBUG: View 0 : 0.662420382166
+2016-08-24 09:11:14,460 DEBUG: View 1 : 0.464968152866
+2016-08-24 09:11:14,495 DEBUG: View 2 : 0.503184713376
+2016-08-24 09:11:14,503 DEBUG: View 3 : 0.528662420382
+2016-08-24 09:11:14,554 DEBUG: Best view : Methyl_
+2016-08-24 09:11:14,751 DEBUG: Start: Iteration 4
+2016-08-24 09:11:14,767 DEBUG: View 0 : 0.433121019108
+2016-08-24 09:11:14,775 DEBUG: View 1 : 0.496815286624
+2016-08-24 09:11:14,811 DEBUG: View 2 : 0.43949044586
+2016-08-24 09:11:14,818 DEBUG: View 3 : 0.547770700637
+2016-08-24 09:11:14,872 DEBUG: Best view : Clinic_
+2016-08-24 09:11:15,126 DEBUG: Start: Iteration 5
+2016-08-24 09:11:15,143 DEBUG: View 0 : 0.503184713376
+2016-08-24 09:11:15,150 DEBUG: View 1 : 0.687898089172
+2016-08-24 09:11:15,187 DEBUG: View 2 : 0.420382165605
+2016-08-24 09:11:15,194 DEBUG: View 3 : 0.592356687898
+2016-08-24 09:11:15,250 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:15,562 DEBUG: Start: Iteration 6
+2016-08-24 09:11:15,578 DEBUG: View 0 : 0.554140127389
+2016-08-24 09:11:15,585 DEBUG: View 1 : 0.515923566879
+2016-08-24 09:11:15,621 DEBUG: View 2 : 0.452229299363
+2016-08-24 09:11:15,629 DEBUG: View 3 : 0.624203821656
+2016-08-24 09:11:15,687 DEBUG: Best view : Clinic_
+2016-08-24 09:11:16,055 DEBUG: Start: Iteration 7
+2016-08-24 09:11:16,071 DEBUG: View 0 : 0.471337579618
+2016-08-24 09:11:16,079 DEBUG: View 1 : 0.388535031847
+2016-08-24 09:11:16,114 DEBUG: View 2 : 0.420382165605
+2016-08-24 09:11:16,122 DEBUG: View 3 : 0.535031847134
+2016-08-24 09:11:16,182 DEBUG: Best view : Clinic_
+2016-08-24 09:11:16,608 DEBUG: Start: Iteration 8
+2016-08-24 09:11:16,624 DEBUG: View 0 : 0.43949044586
+2016-08-24 09:11:16,632 DEBUG: View 1 : 0.726114649682
+2016-08-24 09:11:16,668 DEBUG: View 2 : 0.605095541401
+2016-08-24 09:11:16,676 DEBUG: View 3 : 0.605095541401
+2016-08-24 09:11:16,739 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:17,220 DEBUG: Start: Iteration 9
+2016-08-24 09:11:17,236 DEBUG: View 0 : 0.579617834395
+2016-08-24 09:11:17,244 DEBUG: View 1 : 0.547770700637
+2016-08-24 09:11:17,280 DEBUG: View 2 : 0.388535031847
+2016-08-24 09:11:17,288 DEBUG: View 3 : 0.458598726115
+2016-08-24 09:11:17,352 DEBUG: Best view : Methyl_
+2016-08-24 09:11:17,896 DEBUG: Start: Iteration 10
+2016-08-24 09:11:17,913 DEBUG: View 0 : 0.464968152866
+2016-08-24 09:11:17,921 DEBUG: View 1 : 0.605095541401
+2016-08-24 09:11:17,958 DEBUG: View 2 : 0.528662420382
+2016-08-24 09:11:17,965 DEBUG: View 3 : 0.40127388535
+2016-08-24 09:11:18,034 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:18,635 DEBUG: Start: Iteration 11
+2016-08-24 09:11:18,651 DEBUG: View 0 : 0.363057324841
+2016-08-24 09:11:18,659 DEBUG: View 1 : 0.573248407643
+2016-08-24 09:11:18,695 DEBUG: View 2 : 0.363057324841
+2016-08-24 09:11:18,703 DEBUG: View 3 : 0.445859872611
+2016-08-24 09:11:18,773 DEBUG: Best view : MiRNA__
+2016-08-24 09:11:19,431 DEBUG: Start: Iteration 12
+2016-08-24 09:11:19,447 DEBUG: View 0 : 0.43949044586
+2016-08-24 09:11:19,455 DEBUG: View 1 : 0.375796178344
+2016-08-24 09:11:19,491 DEBUG: View 2 : 0.515923566879
+2016-08-24 09:11:19,499 DEBUG: View 3 : 0.592356687898
+2016-08-24 09:11:19,571 DEBUG: Best view : Clinic_
+2016-08-24 09:11:20,286 INFO: Start: Classification
+2016-08-24 09:11:21,987 INFO: Done: Fold number 2
+2016-08-24 09:11:21,987 INFO: Done: Classification
+2016-08-24 09:11:21,988 INFO: Info: Time for Classification: 85[s]
+2016-08-24 09:11:21,988 INFO: Start: Result Analysis for Mumbo
+2016-08-24 09:11:28,399 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 70.8648800224
+ -On Test : 77.0491803279
+ -On Validation : 81.067961165
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0061572327044
+ - Percentage of time chosen : 0.989
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.00627044025157
+ - Percentage of time chosen : 0.006
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00632704402516
+ - Percentage of time chosen : 0.002
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0060251572327
+ - Percentage of time chosen : 0.003
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00602547770701
+ - Percentage of time chosen : 0.992
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0061847133758
+ - Percentage of time chosen : 0.004
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00568152866242
+ - Percentage of time chosen : 0.0
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00628662420382
+ - Percentage of time chosen : 0.004
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 54.0880503145
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 65.0485436893
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 57.9357449025
+ Accuracy on test : 69.262295082
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 59.8360655738
+ Accuracy on validation : 68.932038835
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 78.640776699
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 64.5675599888
+ Accuracy on test : 67.6229508197
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 59.1194968553
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 69.9029126214
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 78.640776699
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 62.680767536
+ Accuracy on test : 74.5901639344
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 66.6666666667
+ Accuracy on test : 68.8524590164
+ Accuracy on validation : 76.6990291262
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 68.152866242
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 67.4097664544
+ Accuracy on test : 74.1803278689
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 63.5220125786
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 72.8155339806
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 66.8789808917
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 65.2004967352
+ Accuracy on test : 75.8196721311
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 67.9245283019
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 77.6699029126
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 68.152866242
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 78.640776699
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 68.038697272
+ Accuracy on test : 75.4098360656
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 64.1509433962
+ Accuracy on test : 66.393442623
+ Accuracy on validation : 71.8446601942
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 71.974522293
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 68.0627328446
+ Accuracy on test : 73.7704918033
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 71.6981132075
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 70.0636942675
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 81.5533980583
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 70.8809037375
+ Accuracy on test : 76.2295081967
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 69.1823899371
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.4267515924
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.3045707647
+ Accuracy on test : 75.0
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 71.0691823899
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.4267515924
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.2479669911
+ Accuracy on test : 75.4098360656
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 74.213836478
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 82.5242718447
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+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:01:13 0:00:01
+ Fold 2 0:01:23 0:00:01
+ Total 0:02:37 0:00:03
+ So a total classification time of 0:01:25.
+
+
+2016-08-24 09:11:29,450 INFO: Done: Result Analysis
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091129Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091129Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..3715ab22b1a4f8a96fb587e9491c44044540442c
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091129Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091129Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091129Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6cb12d889750d35dde77ef06b3b569c2dcf0e149
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091129Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
@@ -0,0 +1,14060 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 70.8648800224
+ -On Test : 77.0491803279
+ -On Validation : 81.067961165
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0061572327044
+ - Percentage of time chosen : 0.989
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.00627044025157
+ - Percentage of time chosen : 0.006
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00632704402516
+ - Percentage of time chosen : 0.002
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0060251572327
+ - Percentage of time chosen : 0.003
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00602547770701
+ - Percentage of time chosen : 0.992
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0061847133758
+ - Percentage of time chosen : 0.004
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00568152866242
+ - Percentage of time chosen : 0.0
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00628662420382
+ - Percentage of time chosen : 0.004
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 54.0880503145
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 65.0485436893
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 57.9357449025
+ Accuracy on test : 69.262295082
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 59.8360655738
+ Accuracy on validation : 68.932038835
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 78.640776699
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 64.5675599888
+ Accuracy on test : 67.6229508197
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 59.1194968553
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 69.9029126214
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 78.640776699
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 62.680767536
+ Accuracy on test : 74.5901639344
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 66.6666666667
+ Accuracy on test : 68.8524590164
+ Accuracy on validation : 76.6990291262
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 68.152866242
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 67.4097664544
+ Accuracy on test : 74.1803278689
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 63.5220125786
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 72.8155339806
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 66.8789808917
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 65.2004967352
+ Accuracy on test : 75.8196721311
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 67.9245283019
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 77.6699029126
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 68.152866242
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 78.640776699
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 68.038697272
+ Accuracy on test : 75.4098360656
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 64.1509433962
+ Accuracy on test : 66.393442623
+ Accuracy on validation : 71.8446601942
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 71.974522293
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 68.0627328446
+ Accuracy on test : 73.7704918033
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 71.6981132075
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 70.0636942675
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 81.5533980583
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 70.8809037375
+ Accuracy on test : 76.2295081967
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 69.1823899371
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.4267515924
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.3045707647
+ Accuracy on test : 75.0
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 71.0691823899
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.4267515924
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.2479669911
+ Accuracy on test : 75.4098360656
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 74.213836478
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 67.5159235669
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 70.8648800224
+ Accuracy on test : 77.0491803279
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 23
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 24
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 25
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 26
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 27
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 28
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 29
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 30
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 31
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 32
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 33
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 34
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 35
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 36
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 37
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 38
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 39
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 40
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 41
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 42
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
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+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 977
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 978
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 979
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 980
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 981
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 982
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 983
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 984
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 985
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 986
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 987
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 988
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 989
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.0237952169
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:01:13 0:00:01
+ Fold 2 0:01:23 0:00:01
+ Total 0:02:37 0:00:03
+ So a total classification time of 0:01:25.
+
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091625-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091625-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..d062fb389ed665841574f4e497aef0c6316703f8
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091625-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,14246 @@
+2016-08-24 09:16:25,238 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:16:25,238 INFO: Info: Labels used: No, Yes
+2016-08-24 09:16:25,239 INFO: Info: Length of dataset:347
+2016-08-24 09:16:25,240 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:16:25,240 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:16:25,241 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:16:25,241 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:16:25,241 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:16:25,242 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:16:25,242 INFO: Done: Read Database Files
+2016-08-24 09:16:25,242 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:16:25,245 INFO: Done: Determine validation split
+2016-08-24 09:16:25,245 INFO: Start: Determine 2 folds
+2016-08-24 09:16:25,255 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:16:25,255 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:16:25,255 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:16:25,255 INFO: Done: Determine folds
+2016-08-24 09:16:25,255 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:16:25,256 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:16:25,256 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:16:32,562 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:16:32,563 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:16:34,472 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:16:34,473 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:16:51,458 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:16:51,458 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:16:53,197 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:16:53,197 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:17:30,357 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:17:30,357 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:17:30,357 INFO: Start: Fold number 1
+2016-08-24 09:17:32,053 DEBUG: Start: Iteration 1
+2016-08-24 09:17:32,069 DEBUG: View 0 : 0.377358490566
+2016-08-24 09:17:32,077 DEBUG: View 1 : 0.377358490566
+2016-08-24 09:17:32,106 DEBUG: View 2 : 0.622641509434
+2016-08-24 09:17:32,113 DEBUG: View 3 : 0.622641509434
+2016-08-24 09:17:32,155 DEBUG: Best view : Methyl_
+2016-08-24 09:17:32,230 DEBUG: Start: Iteration 2
+2016-08-24 09:17:32,247 DEBUG: View 0 : 0.547169811321
+2016-08-24 09:17:32,255 DEBUG: View 1 : 0.59748427673
+2016-08-24 09:17:32,292 DEBUG: View 2 : 0.547169811321
+2016-08-24 09:17:32,299 DEBUG: View 3 : 0.559748427673
+2016-08-24 09:17:32,344 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:32,475 DEBUG: Start: Iteration 3
+2016-08-24 09:17:32,492 DEBUG: View 0 : 0.641509433962
+2016-08-24 09:17:32,500 DEBUG: View 1 : 0.534591194969
+2016-08-24 09:17:32,536 DEBUG: View 2 : 0.389937106918
+2016-08-24 09:17:32,544 DEBUG: View 3 : 0.59748427673
+2016-08-24 09:17:32,597 DEBUG: Best view : Methyl_
+2016-08-24 09:17:32,792 DEBUG: Start: Iteration 4
+2016-08-24 09:17:32,808 DEBUG: View 0 : 0.389937106918
+2016-08-24 09:17:32,816 DEBUG: View 1 : 0.62893081761
+2016-08-24 09:17:32,852 DEBUG: View 2 : 0.389937106918
+2016-08-24 09:17:32,860 DEBUG: View 3 : 0.446540880503
+2016-08-24 09:17:32,915 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:33,165 DEBUG: Start: Iteration 5
+2016-08-24 09:17:33,182 DEBUG: View 0 : 0.509433962264
+2016-08-24 09:17:33,189 DEBUG: View 1 : 0.603773584906
+2016-08-24 09:17:33,226 DEBUG: View 2 : 0.62893081761
+2016-08-24 09:17:33,233 DEBUG: View 3 : 0.503144654088
+2016-08-24 09:17:33,291 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:33,599 DEBUG: Start: Iteration 6
+2016-08-24 09:17:33,615 DEBUG: View 0 : 0.421383647799
+2016-08-24 09:17:33,623 DEBUG: View 1 : 0.572327044025
+2016-08-24 09:17:33,660 DEBUG: View 2 : 0.553459119497
+2016-08-24 09:17:33,668 DEBUG: View 3 : 0.490566037736
+2016-08-24 09:17:33,727 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:34,092 DEBUG: Start: Iteration 7
+2016-08-24 09:17:34,109 DEBUG: View 0 : 0.553459119497
+2016-08-24 09:17:34,116 DEBUG: View 1 : 0.603773584906
+2016-08-24 09:17:34,153 DEBUG: View 2 : 0.610062893082
+2016-08-24 09:17:34,161 DEBUG: View 3 : 0.433962264151
+2016-08-24 09:17:34,223 DEBUG: Best view : RANSeq_
+2016-08-24 09:17:34,661 DEBUG: Start: Iteration 8
+2016-08-24 09:17:34,677 DEBUG: View 0 : 0.522012578616
+2016-08-24 09:17:34,685 DEBUG: View 1 : 0.654088050314
+2016-08-24 09:17:34,721 DEBUG: View 2 : 0.48427672956
+2016-08-24 09:17:34,729 DEBUG: View 3 : 0.477987421384
+2016-08-24 09:17:34,793 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:35,289 DEBUG: Start: Iteration 9
+2016-08-24 09:17:35,305 DEBUG: View 0 : 0.358490566038
+2016-08-24 09:17:35,313 DEBUG: View 1 : 0.534591194969
+2016-08-24 09:17:35,350 DEBUG: View 2 : 0.522012578616
+2016-08-24 09:17:35,357 DEBUG: View 3 : 0.704402515723
+2016-08-24 09:17:35,424 DEBUG: Best view : Clinic_
+2016-08-24 09:17:35,976 DEBUG: Start: Iteration 10
+2016-08-24 09:17:35,992 DEBUG: View 0 : 0.666666666667
+2016-08-24 09:17:36,000 DEBUG: View 1 : 0.616352201258
+2016-08-24 09:17:36,037 DEBUG: View 2 : 0.415094339623
+2016-08-24 09:17:36,044 DEBUG: View 3 : 0.465408805031
+2016-08-24 09:17:36,112 DEBUG: Best view : Methyl_
+2016-08-24 09:17:36,725 DEBUG: Start: Iteration 11
+2016-08-24 09:17:36,742 DEBUG: View 0 : 0.427672955975
+2016-08-24 09:17:36,749 DEBUG: View 1 : 0.534591194969
+2016-08-24 09:17:36,786 DEBUG: View 2 : 0.446540880503
+2016-08-24 09:17:36,793 DEBUG: View 3 : 0.522012578616
+2016-08-24 09:17:36,864 DEBUG: Best view : Clinic_
+2016-08-24 09:17:37,731 DEBUG: Start: Iteration 12
+2016-08-24 09:17:37,748 DEBUG: View 0 : 0.440251572327
+2016-08-24 09:17:37,756 DEBUG: View 1 : 0.37106918239
+2016-08-24 09:17:37,793 DEBUG: View 2 : 0.553459119497
+2016-08-24 09:17:37,800 DEBUG: View 3 : 0.509433962264
+2016-08-24 09:17:37,874 DEBUG: Best view : RANSeq_
+2016-08-24 09:17:38,629 INFO: Start: Classification
+2016-08-24 09:17:40,368 INFO: Done: Fold number 1
+2016-08-24 09:17:40,368 INFO: Start: Fold number 2
+2016-08-24 09:17:41,934 DEBUG: Start: Iteration 1
+2016-08-24 09:17:41,952 DEBUG: View 0 : 0.5
+2016-08-24 09:17:41,960 DEBUG: View 1 : 0.379746835443
+2016-08-24 09:17:41,988 DEBUG: View 2 : 0.620253164557
+2016-08-24 09:17:41,996 DEBUG: View 3 : 0.620253164557
+2016-08-24 09:17:42,041 DEBUG: Best view : Methyl_
+2016-08-24 09:17:42,117 DEBUG: Start: Iteration 2
+2016-08-24 09:17:42,133 DEBUG: View 0 : 0.436708860759
+2016-08-24 09:17:42,141 DEBUG: View 1 : 0.354430379747
+2016-08-24 09:17:42,178 DEBUG: View 2 : 0.430379746835
+2016-08-24 09:17:42,185 DEBUG: View 3 : 0.556962025316
+2016-08-24 09:17:42,230 DEBUG: Best view : Clinic_
+2016-08-24 09:17:42,361 DEBUG: Start: Iteration 3
+2016-08-24 09:17:42,377 DEBUG: View 0 : 0.481012658228
+2016-08-24 09:17:42,385 DEBUG: View 1 : 0.373417721519
+2016-08-24 09:17:42,421 DEBUG: View 2 : 0.386075949367
+2016-08-24 09:17:42,429 DEBUG: View 3 : 0.386075949367
+2016-08-24 09:17:42,429 WARNING: All bad for iteration 2
+2016-08-24 09:17:42,482 DEBUG: Best view : Methyl_
+2016-08-24 09:17:42,675 DEBUG: Start: Iteration 4
+2016-08-24 09:17:42,692 DEBUG: View 0 : 0.506329113924
+2016-08-24 09:17:42,699 DEBUG: View 1 : 0.544303797468
+2016-08-24 09:17:42,735 DEBUG: View 2 : 0.550632911392
+2016-08-24 09:17:42,743 DEBUG: View 3 : 0.626582278481
+2016-08-24 09:17:42,798 DEBUG: Best view : Clinic_
+2016-08-24 09:17:43,047 DEBUG: Start: Iteration 5
+2016-08-24 09:17:43,063 DEBUG: View 0 : 0.588607594937
+2016-08-24 09:17:43,071 DEBUG: View 1 : 0.601265822785
+2016-08-24 09:17:43,107 DEBUG: View 2 : 0.443037974684
+2016-08-24 09:17:43,114 DEBUG: View 3 : 0.544303797468
+2016-08-24 09:17:43,171 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:43,477 DEBUG: Start: Iteration 6
+2016-08-24 09:17:43,494 DEBUG: View 0 : 0.481012658228
+2016-08-24 09:17:43,501 DEBUG: View 1 : 0.601265822785
+2016-08-24 09:17:43,538 DEBUG: View 2 : 0.493670886076
+2016-08-24 09:17:43,545 DEBUG: View 3 : 0.493670886076
+2016-08-24 09:17:43,605 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:43,969 DEBUG: Start: Iteration 7
+2016-08-24 09:17:43,985 DEBUG: View 0 : 0.322784810127
+2016-08-24 09:17:43,993 DEBUG: View 1 : 0.474683544304
+2016-08-24 09:17:44,029 DEBUG: View 2 : 0.417721518987
+2016-08-24 09:17:44,036 DEBUG: View 3 : 0.601265822785
+2016-08-24 09:17:44,097 DEBUG: Best view : Clinic_
+2016-08-24 09:17:44,516 DEBUG: Start: Iteration 8
+2016-08-24 09:17:44,533 DEBUG: View 0 : 0.525316455696
+2016-08-24 09:17:44,540 DEBUG: View 1 : 0.632911392405
+2016-08-24 09:17:44,577 DEBUG: View 2 : 0.607594936709
+2016-08-24 09:17:44,584 DEBUG: View 3 : 0.411392405063
+2016-08-24 09:17:44,648 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:45,123 DEBUG: Start: Iteration 9
+2016-08-24 09:17:45,139 DEBUG: View 0 : 0.677215189873
+2016-08-24 09:17:45,147 DEBUG: View 1 : 0.398734177215
+2016-08-24 09:17:45,183 DEBUG: View 2 : 0.575949367089
+2016-08-24 09:17:45,191 DEBUG: View 3 : 0.462025316456
+2016-08-24 09:17:45,257 DEBUG: Best view : Methyl_
+2016-08-24 09:17:45,800 DEBUG: Start: Iteration 10
+2016-08-24 09:17:45,817 DEBUG: View 0 : 0.664556962025
+2016-08-24 09:17:45,825 DEBUG: View 1 : 0.632911392405
+2016-08-24 09:17:45,862 DEBUG: View 2 : 0.613924050633
+2016-08-24 09:17:45,869 DEBUG: View 3 : 0.601265822785
+2016-08-24 09:17:45,941 DEBUG: Best view : Methyl_
+2016-08-24 09:17:46,549 DEBUG: Start: Iteration 11
+2016-08-24 09:17:46,566 DEBUG: View 0 : 0.506329113924
+2016-08-24 09:17:46,573 DEBUG: View 1 : 0.373417721519
+2016-08-24 09:17:46,610 DEBUG: View 2 : 0.620253164557
+2016-08-24 09:17:46,617 DEBUG: View 3 : 0.563291139241
+2016-08-24 09:17:46,688 DEBUG: Best view : RANSeq_
+2016-08-24 09:17:47,371 DEBUG: Start: Iteration 12
+2016-08-24 09:17:47,390 DEBUG: View 0 : 0.405063291139
+2016-08-24 09:17:47,399 DEBUG: View 1 : 0.658227848101
+2016-08-24 09:17:47,435 DEBUG: View 2 : 0.620253164557
+2016-08-24 09:17:47,443 DEBUG: View 3 : 0.626582278481
+2016-08-24 09:17:47,517 DEBUG: Best view : MiRNA__
+2016-08-24 09:17:48,252 INFO: Start: Classification
+2016-08-24 09:17:49,990 INFO: Done: Fold number 2
+2016-08-24 09:17:49,990 INFO: Done: Classification
+2016-08-24 09:17:49,990 INFO: Info: Time for Classification: 84[s]
+2016-08-24 09:17:49,990 INFO: Start: Result Analysis for Mumbo
+2016-08-24 09:17:55,375 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 68.4519544622
+ -On Test : 76.6393442623
+ -On Validation : 76.213592233
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.0075 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.0065 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00585534591195
+ - Percentage of time chosen : 0.991
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.00662893081761
+ - Percentage of time chosen : 0.005
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00616352201258
+ - Percentage of time chosen : 0.002
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00633333333333
+ - Percentage of time chosen : 0.002
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00609493670886
+ - Percentage of time chosen : 0.992
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0060253164557
+ - Percentage of time chosen : 0.004
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00637974683544
+ - Percentage of time chosen : 0.001
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00649367088608
+ - Percentage of time chosen : 0.003
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 59.748427673
+ Accuracy on test : 53.2786885246
+ Accuracy on validation : 67.9611650485
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 55.6962025316
+ Accuracy on test : 64.7540983607
+ Accuracy on validation : 63.1067961165
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 57.7223151023
+ Accuracy on test : 59.0163934426
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 64.1509433962
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 75.7281553398
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 55.6962025316
+ Accuracy on test : 64.7540983607
+ Accuracy on validation : 63.1067961165
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 59.9235729639
+ Accuracy on test : 67.2131147541
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.6582278481
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 69.9029126214
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 62.7756548046
+ Accuracy on test : 72.5409836066
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 63.5220125786
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 63.2911392405
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 70.8737864078
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 63.4065759096
+ Accuracy on test : 72.5409836066
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 69.9029126214
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 62.4591991084
+ Accuracy on test : 72.5409836066
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 64.1509433962
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 70.8737864078
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.088129926
+ Accuracy on test : 71.7213114754
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 65.1898734177
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 64.0414775894
+ Accuracy on test : 73.3606557377
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 64.7798742138
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 67.7215189873
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 75.7281553398
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 66.2506966006
+ Accuracy on test : 72.9508196721
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 66.0377358491
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 76.6990291262
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 70.8860759494
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 74.7572815534
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 68.4619058992
+ Accuracy on test : 77.868852459
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 70.4402515723
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 72.7848101266
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 78.640776699
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 71.6125308495
+ Accuracy on test : 75.8196721311
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 69.1823899371
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 78.640776699
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 67.7215189873
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 68.4519544622
+ Accuracy on test : 76.6393442623
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 23
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 24
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 25
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 26
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 27
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 28
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 29
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 30
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 31
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 32
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 33
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 34
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 35
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 36
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 37
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 38
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 39
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 40
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 41
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 42
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 43
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 44
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
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+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:01:13 0:00:01
+ Fold 2 0:01:22 0:00:01
+ Total 0:02:36 0:00:03
+ So a total classification time of 0:01:24.
+
+
+2016-08-24 09:17:56,318 INFO: Done: Result Analysis
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091756Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091756Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..f331f2fb198ab0807813fcc2584f9e9b11772d4b
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091756Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091756Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091756Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..616b19abd831a756d5b4fba15edca36223933097
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-091756Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
@@ -0,0 +1,14060 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 68.4519544622
+ -On Test : 76.6393442623
+ -On Validation : 76.213592233
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.0075 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.0065 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00585534591195
+ - Percentage of time chosen : 0.991
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.00662893081761
+ - Percentage of time chosen : 0.005
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00616352201258
+ - Percentage of time chosen : 0.002
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00633333333333
+ - Percentage of time chosen : 0.002
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00609493670886
+ - Percentage of time chosen : 0.992
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0060253164557
+ - Percentage of time chosen : 0.004
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00637974683544
+ - Percentage of time chosen : 0.001
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00649367088608
+ - Percentage of time chosen : 0.003
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 59.748427673
+ Accuracy on test : 53.2786885246
+ Accuracy on validation : 67.9611650485
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 55.6962025316
+ Accuracy on test : 64.7540983607
+ Accuracy on validation : 63.1067961165
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 57.7223151023
+ Accuracy on test : 59.0163934426
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 64.1509433962
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 75.7281553398
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 55.6962025316
+ Accuracy on test : 64.7540983607
+ Accuracy on validation : 63.1067961165
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 59.9235729639
+ Accuracy on test : 67.2131147541
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.6582278481
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 69.9029126214
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 62.7756548046
+ Accuracy on test : 72.5409836066
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 63.5220125786
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 63.2911392405
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 70.8737864078
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 63.4065759096
+ Accuracy on test : 72.5409836066
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 69.9029126214
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 62.4591991084
+ Accuracy on test : 72.5409836066
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 64.1509433962
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 70.8737864078
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.088129926
+ Accuracy on test : 71.7213114754
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 62.893081761
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 65.1898734177
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 64.0414775894
+ Accuracy on test : 73.3606557377
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 64.7798742138
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 67.7215189873
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 75.7281553398
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 66.2506966006
+ Accuracy on test : 72.9508196721
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 66.0377358491
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 76.6990291262
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 70.8860759494
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 74.7572815534
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 68.4619058992
+ Accuracy on test : 77.868852459
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 70.4402515723
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 72.7848101266
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 78.640776699
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 71.6125308495
+ Accuracy on test : 75.8196721311
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 69.1823899371
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 78.640776699
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 67.7215189873
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 68.4519544622
+ Accuracy on test : 76.6393442623
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 23
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 24
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 25
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 26
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 27
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 28
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 29
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 30
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 31
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 32
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 33
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 34
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
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+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 981
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 982
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 983
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 984
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 985
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 986
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 987
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 988
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 989
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.0253164557
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1447336995
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:01:13 0:00:01
+ Fold 2 0:01:22 0:00:01
+ Total 0:02:36 0:00:03
+ So a total classification time of 0:01:24.
+
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092030-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092030-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..3426f1a2d0c9e2d5664b919f9344c18a2051ad40
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092030-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,14248 @@
+2016-08-24 09:20:30,659 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:20:30,660 INFO: Info: Labels used: No, Yes
+2016-08-24 09:20:30,660 INFO: Info: Length of dataset:347
+2016-08-24 09:20:30,661 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:20:30,661 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:20:30,662 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:20:30,662 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:20:30,663 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:20:30,663 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:20:30,663 INFO: Done: Read Database Files
+2016-08-24 09:20:30,663 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:20:30,667 INFO: Done: Determine validation split
+2016-08-24 09:20:30,667 INFO: Start: Determine 2 folds
+2016-08-24 09:20:30,678 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:20:30,678 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:20:30,678 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:20:30,678 INFO: Done: Determine folds
+2016-08-24 09:20:30,678 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:20:30,678 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:20:30,679 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:20:37,995 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:20:37,995 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:20:39,915 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:20:39,916 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:20:56,530 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:20:56,530 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:20:58,283 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:20:58,284 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:21:35,801 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:21:35,802 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:21:35,802 INFO: Start: Fold number 1
+2016-08-24 09:21:37,555 DEBUG: Start: Iteration 1
+2016-08-24 09:21:37,575 DEBUG: View 0 : 0.375
+2016-08-24 09:21:37,583 DEBUG: View 1 : 0.625
+2016-08-24 09:21:37,620 DEBUG: View 2 : 0.375
+2016-08-24 09:21:37,628 DEBUG: View 3 : 0.625
+2016-08-24 09:21:37,670 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:37,743 DEBUG: Start: Iteration 2
+2016-08-24 09:21:37,760 DEBUG: View 0 : 0.4625
+2016-08-24 09:21:37,768 DEBUG: View 1 : 0.6875
+2016-08-24 09:21:37,805 DEBUG: View 2 : 0.5375
+2016-08-24 09:21:37,812 DEBUG: View 3 : 0.39375
+2016-08-24 09:21:37,858 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:37,989 DEBUG: Start: Iteration 3
+2016-08-24 09:21:38,006 DEBUG: View 0 : 0.43125
+2016-08-24 09:21:38,014 DEBUG: View 1 : 0.7
+2016-08-24 09:21:38,050 DEBUG: View 2 : 0.41875
+2016-08-24 09:21:38,058 DEBUG: View 3 : 0.38125
+2016-08-24 09:21:38,112 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:38,303 DEBUG: Start: Iteration 4
+2016-08-24 09:21:38,320 DEBUG: View 0 : 0.425
+2016-08-24 09:21:38,328 DEBUG: View 1 : 0.63125
+2016-08-24 09:21:38,365 DEBUG: View 2 : 0.525
+2016-08-24 09:21:38,372 DEBUG: View 3 : 0.44375
+2016-08-24 09:21:38,429 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:38,678 DEBUG: Start: Iteration 5
+2016-08-24 09:21:38,695 DEBUG: View 0 : 0.56875
+2016-08-24 09:21:38,703 DEBUG: View 1 : 0.45625
+2016-08-24 09:21:38,739 DEBUG: View 2 : 0.575
+2016-08-24 09:21:38,747 DEBUG: View 3 : 0.5125
+2016-08-24 09:21:38,806 DEBUG: Best view : RANSeq_
+2016-08-24 09:21:39,130 DEBUG: Start: Iteration 6
+2016-08-24 09:21:39,147 DEBUG: View 0 : 0.4625
+2016-08-24 09:21:39,155 DEBUG: View 1 : 0.4375
+2016-08-24 09:21:39,192 DEBUG: View 2 : 0.54375
+2016-08-24 09:21:39,199 DEBUG: View 3 : 0.3875
+2016-08-24 09:21:39,260 DEBUG: Best view : RANSeq_
+2016-08-24 09:21:39,657 DEBUG: Start: Iteration 7
+2016-08-24 09:21:39,673 DEBUG: View 0 : 0.60625
+2016-08-24 09:21:39,681 DEBUG: View 1 : 0.4
+2016-08-24 09:21:39,717 DEBUG: View 2 : 0.54375
+2016-08-24 09:21:39,725 DEBUG: View 3 : 0.6125
+2016-08-24 09:21:39,788 DEBUG: Best view : Methyl_
+2016-08-24 09:21:40,246 DEBUG: Start: Iteration 8
+2016-08-24 09:21:40,263 DEBUG: View 0 : 0.43125
+2016-08-24 09:21:40,271 DEBUG: View 1 : 0.7
+2016-08-24 09:21:40,307 DEBUG: View 2 : 0.44375
+2016-08-24 09:21:40,315 DEBUG: View 3 : 0.50625
+2016-08-24 09:21:40,381 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:40,897 DEBUG: Start: Iteration 9
+2016-08-24 09:21:40,914 DEBUG: View 0 : 0.41875
+2016-08-24 09:21:40,922 DEBUG: View 1 : 0.30625
+2016-08-24 09:21:40,961 DEBUG: View 2 : 0.35625
+2016-08-24 09:21:40,968 DEBUG: View 3 : 0.425
+2016-08-24 09:21:40,968 WARNING: All bad for iteration 8
+2016-08-24 09:21:41,036 DEBUG: Best view : Clinic_
+2016-08-24 09:21:41,611 DEBUG: Start: Iteration 10
+2016-08-24 09:21:41,628 DEBUG: View 0 : 0.70625
+2016-08-24 09:21:41,635 DEBUG: View 1 : 0.6375
+2016-08-24 09:21:41,672 DEBUG: View 2 : 0.55625
+2016-08-24 09:21:41,679 DEBUG: View 3 : 0.39375
+2016-08-24 09:21:41,750 DEBUG: Best view : Methyl_
+2016-08-24 09:21:42,388 DEBUG: Start: Iteration 11
+2016-08-24 09:21:42,404 DEBUG: View 0 : 0.40625
+2016-08-24 09:21:42,412 DEBUG: View 1 : 0.79375
+2016-08-24 09:21:42,449 DEBUG: View 2 : 0.425
+2016-08-24 09:21:42,456 DEBUG: View 3 : 0.525
+2016-08-24 09:21:42,530 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:43,407 DEBUG: Start: Iteration 12
+2016-08-24 09:21:43,424 DEBUG: View 0 : 0.4875
+2016-08-24 09:21:43,432 DEBUG: View 1 : 0.4625
+2016-08-24 09:21:43,468 DEBUG: View 2 : 0.43125
+2016-08-24 09:21:43,475 DEBUG: View 3 : 0.44375
+2016-08-24 09:21:43,476 WARNING: All bad for iteration 11
+2016-08-24 09:21:43,550 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:44,302 INFO: Start: Classification
+2016-08-24 09:21:46,079 INFO: Done: Fold number 1
+2016-08-24 09:21:46,079 INFO: Start: Fold number 2
+2016-08-24 09:21:47,689 DEBUG: Start: Iteration 1
+2016-08-24 09:21:47,704 DEBUG: View 0 : 0.37037037037
+2016-08-24 09:21:47,712 DEBUG: View 1 : 0.364197530864
+2016-08-24 09:21:47,741 DEBUG: View 2 : 0.62962962963
+2016-08-24 09:21:47,748 DEBUG: View 3 : 0.37037037037
+2016-08-24 09:21:47,790 DEBUG: Best view : Methyl_
+2016-08-24 09:21:47,866 DEBUG: Start: Iteration 2
+2016-08-24 09:21:47,883 DEBUG: View 0 : 0.475308641975
+2016-08-24 09:21:47,891 DEBUG: View 1 : 0.345679012346
+2016-08-24 09:21:47,928 DEBUG: View 2 : 0.518518518519
+2016-08-24 09:21:47,935 DEBUG: View 3 : 0.574074074074
+2016-08-24 09:21:47,981 DEBUG: Best view : Clinic_
+2016-08-24 09:21:48,116 DEBUG: Start: Iteration 3
+2016-08-24 09:21:48,133 DEBUG: View 0 : 0.530864197531
+2016-08-24 09:21:48,141 DEBUG: View 1 : 0.561728395062
+2016-08-24 09:21:48,177 DEBUG: View 2 : 0.506172839506
+2016-08-24 09:21:48,185 DEBUG: View 3 : 0.518518518519
+2016-08-24 09:21:48,239 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:48,435 DEBUG: Start: Iteration 4
+2016-08-24 09:21:48,452 DEBUG: View 0 : 0.450617283951
+2016-08-24 09:21:48,460 DEBUG: View 1 : 0.432098765432
+2016-08-24 09:21:48,497 DEBUG: View 2 : 0.481481481481
+2016-08-24 09:21:48,504 DEBUG: View 3 : 0.41975308642
+2016-08-24 09:21:48,504 WARNING: All bad for iteration 3
+2016-08-24 09:21:48,560 DEBUG: Best view : Clinic_
+2016-08-24 09:21:48,815 DEBUG: Start: Iteration 5
+2016-08-24 09:21:48,831 DEBUG: View 0 : 0.666666666667
+2016-08-24 09:21:48,839 DEBUG: View 1 : 0.487654320988
+2016-08-24 09:21:48,876 DEBUG: View 2 : 0.512345679012
+2016-08-24 09:21:48,884 DEBUG: View 3 : 0.41975308642
+2016-08-24 09:21:48,942 DEBUG: Best view : Methyl_
+2016-08-24 09:21:49,259 DEBUG: Start: Iteration 6
+2016-08-24 09:21:49,275 DEBUG: View 0 : 0.567901234568
+2016-08-24 09:21:49,283 DEBUG: View 1 : 0.703703703704
+2016-08-24 09:21:49,320 DEBUG: View 2 : 0.432098765432
+2016-08-24 09:21:49,328 DEBUG: View 3 : 0.604938271605
+2016-08-24 09:21:49,389 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:49,764 DEBUG: Start: Iteration 7
+2016-08-24 09:21:49,781 DEBUG: View 0 : 0.41975308642
+2016-08-24 09:21:49,789 DEBUG: View 1 : 0.617283950617
+2016-08-24 09:21:49,825 DEBUG: View 2 : 0.438271604938
+2016-08-24 09:21:49,833 DEBUG: View 3 : 0.382716049383
+2016-08-24 09:21:49,896 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:50,330 DEBUG: Start: Iteration 8
+2016-08-24 09:21:50,347 DEBUG: View 0 : 0.524691358025
+2016-08-24 09:21:50,355 DEBUG: View 1 : 0.574074074074
+2016-08-24 09:21:50,391 DEBUG: View 2 : 0.469135802469
+2016-08-24 09:21:50,398 DEBUG: View 3 : 0.432098765432
+2016-08-24 09:21:50,464 DEBUG: Best view : MiRNA__
+2016-08-24 09:21:50,959 DEBUG: Start: Iteration 9
+2016-08-24 09:21:50,975 DEBUG: View 0 : 0.475308641975
+2016-08-24 09:21:50,983 DEBUG: View 1 : 0.432098765432
+2016-08-24 09:21:51,020 DEBUG: View 2 : 0.456790123457
+2016-08-24 09:21:51,028 DEBUG: View 3 : 0.524691358025
+2016-08-24 09:21:51,095 DEBUG: Best view : Clinic_
+2016-08-24 09:21:51,646 DEBUG: Start: Iteration 10
+2016-08-24 09:21:51,663 DEBUG: View 0 : 0.524691358025
+2016-08-24 09:21:51,670 DEBUG: View 1 : 0.395061728395
+2016-08-24 09:21:51,707 DEBUG: View 2 : 0.475308641975
+2016-08-24 09:21:51,714 DEBUG: View 3 : 0.537037037037
+2016-08-24 09:21:51,784 DEBUG: Best view : Methyl_
+2016-08-24 09:21:52,399 DEBUG: Start: Iteration 11
+2016-08-24 09:21:52,416 DEBUG: View 0 : 0.666666666667
+2016-08-24 09:21:52,424 DEBUG: View 1 : 0.574074074074
+2016-08-24 09:21:52,460 DEBUG: View 2 : 0.555555555556
+2016-08-24 09:21:52,467 DEBUG: View 3 : 0.5
+2016-08-24 09:21:52,539 DEBUG: Best view : Methyl_
+2016-08-24 09:21:53,381 DEBUG: Start: Iteration 12
+2016-08-24 09:21:53,398 DEBUG: View 0 : 0.512345679012
+2016-08-24 09:21:53,406 DEBUG: View 1 : 0.475308641975
+2016-08-24 09:21:53,442 DEBUG: View 2 : 0.586419753086
+2016-08-24 09:21:53,450 DEBUG: View 3 : 0.456790123457
+2016-08-24 09:21:53,524 DEBUG: Best view : RANSeq_
+2016-08-24 09:21:54,276 INFO: Start: Classification
+2016-08-24 09:21:56,037 INFO: Done: Fold number 2
+2016-08-24 09:21:56,037 INFO: Done: Classification
+2016-08-24 09:21:56,037 INFO: Info: Time for Classification: 85[s]
+2016-08-24 09:21:56,037 INFO: Start: Result Analysis for Mumbo
+2016-08-24 09:22:01,520 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 76.1072530864
+ -On Test : 79.0983606557
+ -On Validation : 83.0097087379
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.008 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00578125
+ - Percentage of time chosen : 0.99
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0068375
+ - Percentage of time chosen : 0.007
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00573125
+ - Percentage of time chosen : 0.002
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00565
+ - Percentage of time chosen : 0.001
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00618518518519
+ - Percentage of time chosen : 0.992
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.00596296296296
+ - Percentage of time chosen : 0.004
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00606172839506
+ - Percentage of time chosen : 0.001
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00574074074074
+ - Percentage of time chosen : 0.003
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 68.75
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 57.4074074074
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 70.8737864078
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.0787037037
+ Accuracy on test : 72.5409836066
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 70.0
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 57.4074074074
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 70.8737864078
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 63.7037037037
+ Accuracy on test : 72.9508196721
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 69.375
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 57.4074074074
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 70.8737864078
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.3912037037
+ Accuracy on test : 74.5901639344
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 69.375
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 60.4938271605
+ Accuracy on test : 70.4918032787
+ Accuracy on validation : 71.8446601942
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 64.9344135802
+ Accuracy on test : 75.8196721311
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 68.75
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 67.2839506173
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 68.0169753086
+ Accuracy on test : 75.4098360656
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 70.0
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 78.640776699
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 66.049382716
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 68.024691358
+ Accuracy on test : 74.5901639344
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 75.625
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 67.2839506173
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 71.8446601942
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 71.4544753086
+ Accuracy on test : 77.4590163934
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 75.625
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 66.049382716
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 73.786407767
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 70.837191358
+ Accuracy on test : 77.4590163934
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 73.75
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 81.5533980583
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 70.987654321
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 74.7572815534
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 72.3688271605
+ Accuracy on test : 76.6393442623
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 79.375
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 74.0740740741
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 77.6699029126
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 76.724537037
+ Accuracy on test : 80.3278688525
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 79.375
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 72.8395061728
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 78.640776699
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 76.1072530864
+ Accuracy on test : 79.0983606557
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 23
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 24
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 25
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 26
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 27
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 28
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 29
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 30
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 31
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 32
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 33
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 34
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 35
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 36
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 37
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 38
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 39
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 40
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 41
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 42
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 43
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 44
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 45
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 46
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 47
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 48
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 49
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 50
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 51
+ Fold 1
+ Accuracy on train : 62.5
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+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 962
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 963
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 964
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 965
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 966
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 967
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 968
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 969
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 970
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 971
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 972
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 973
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 974
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 975
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 976
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 977
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 978
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 979
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 980
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 981
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 982
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 983
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 984
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 985
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 986
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 987
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 988
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 989
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:01:13 0:00:01
+ Fold 2 0:01:23 0:00:01
+ Total 0:02:37 0:00:03
+ So a total classification time of 0:01:25.
+
+
+2016-08-24 09:22:02,444 INFO: Done: Result Analysis
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092202Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092202Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..1e1c6469e67fa516d2b8346608b162c9c1559562
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092202Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092202Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092202Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..42ada44b205287f7dbad67dc7101e17dc06f06be
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092202Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
@@ -0,0 +1,14060 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 76.1072530864
+ -On Test : 79.0983606557
+ -On Validation : 83.0097087379
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.008 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00578125
+ - Percentage of time chosen : 0.99
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0068375
+ - Percentage of time chosen : 0.007
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00573125
+ - Percentage of time chosen : 0.002
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00565
+ - Percentage of time chosen : 0.001
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.00618518518519
+ - Percentage of time chosen : 0.992
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.00596296296296
+ - Percentage of time chosen : 0.004
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.00606172839506
+ - Percentage of time chosen : 0.001
+ - On Clinic_ :
+ - Mean average Accuracy : 0.00574074074074
+ - Percentage of time chosen : 0.003
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 68.75
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 57.4074074074
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 70.8737864078
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.0787037037
+ Accuracy on test : 72.5409836066
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 70.0
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 57.4074074074
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 70.8737864078
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 63.7037037037
+ Accuracy on test : 72.9508196721
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 69.375
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 57.4074074074
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 70.8737864078
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.3912037037
+ Accuracy on test : 74.5901639344
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 69.375
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 60.4938271605
+ Accuracy on test : 70.4918032787
+ Accuracy on validation : 71.8446601942
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 64.9344135802
+ Accuracy on test : 75.8196721311
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 68.75
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 67.2839506173
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 68.0169753086
+ Accuracy on test : 75.4098360656
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 70.0
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 78.640776699
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 66.049382716
+ Accuracy on test : 72.131147541
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+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 972
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 973
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 974
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 975
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 976
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 977
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 978
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 979
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 980
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 981
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 982
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 983
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 984
+ Fold 1
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+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 985
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 986
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+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 987
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+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 988
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 989
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 62.5
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.962962963
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.7314814815
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:01:13 0:00:01
+ Fold 2 0:01:23 0:00:01
+ Total 0:02:37 0:00:03
+ So a total classification time of 0:01:25.
+
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092301-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092301-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..8ef0a66520ea0fc6696ae83bbfbad58b7353302f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092301-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,557 @@
+2016-08-24 09:23:01,452 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:23:01,453 INFO: Info: Labels used: No, Yes
+2016-08-24 09:23:01,453 INFO: Info: Length of dataset:347
+2016-08-24 09:23:01,454 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:23:01,455 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:23:01,455 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:23:01,455 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:23:01,456 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:23:01,456 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:23:01,456 INFO: Done: Read Database Files
+2016-08-24 09:23:01,456 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:23:01,460 INFO: Done: Determine validation split
+2016-08-24 09:23:01,460 INFO: Start: Determine 2 folds
+2016-08-24 09:23:01,469 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:23:01,469 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:23:01,469 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:23:01,469 INFO: Done: Determine folds
+2016-08-24 09:23:01,469 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:23:01,469 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:23:01,469 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:23:08,825 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:23:08,826 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:23:10,814 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:23:10,814 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:23:27,482 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:23:27,482 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:23:29,240 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:23:29,241 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:24:07,505 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:24:07,505 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:24:07,505 INFO: Start: Fold number 1
+2016-08-24 09:24:09,143 DEBUG: Start: Iteration 1
+2016-08-24 09:24:09,163 DEBUG: View 0 : 0.596153846154
+2016-08-24 09:24:09,171 DEBUG: View 1 : 0.384615384615
+2016-08-24 09:24:09,198 DEBUG: View 2 : 0.615384615385
+2016-08-24 09:24:09,206 DEBUG: View 3 : 0.615384615385
+2016-08-24 09:24:09,247 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:09,317 DEBUG: Start: Iteration 2
+2016-08-24 09:24:09,335 DEBUG: View 0 : 0.5
+2016-08-24 09:24:09,342 DEBUG: View 1 : 0.288461538462
+2016-08-24 09:24:09,379 DEBUG: View 2 : 0.5
+2016-08-24 09:24:09,386 DEBUG: View 3 : 0.410256410256
+2016-08-24 09:24:09,432 DEBUG: Best view : Methyl_
+2016-08-24 09:24:09,567 DEBUG: Start: Iteration 3
+2016-08-24 09:24:09,584 DEBUG: View 0 : 0.461538461538
+2016-08-24 09:24:09,592 DEBUG: View 1 : 0.621794871795
+2016-08-24 09:24:09,628 DEBUG: View 2 : 0.532051282051
+2016-08-24 09:24:09,636 DEBUG: View 3 : 0.621794871795
+2016-08-24 09:24:09,689 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:09,884 DEBUG: Start: Iteration 4
+2016-08-24 09:24:09,900 DEBUG: View 0 : 0.544871794872
+2016-08-24 09:24:09,908 DEBUG: View 1 : 0.474358974359
+2016-08-24 09:24:09,944 DEBUG: View 2 : 0.442307692308
+2016-08-24 09:24:09,952 DEBUG: View 3 : 0.423076923077
+2016-08-24 09:24:10,007 DEBUG: Best view : Methyl_
+2016-08-24 09:24:10,258 DEBUG: Start: Iteration 5
+2016-08-24 09:24:10,275 DEBUG: View 0 : 0.49358974359
+2016-08-24 09:24:10,282 DEBUG: View 1 : 0.557692307692
+2016-08-24 09:24:10,319 DEBUG: View 2 : 0.596153846154
+2016-08-24 09:24:10,327 DEBUG: View 3 : 0.429487179487
+2016-08-24 09:24:10,384 DEBUG: Best view : RANSeq_
+2016-08-24 09:24:10,714 DEBUG: Start: Iteration 6
+2016-08-24 09:24:10,731 DEBUG: View 0 : 0.544871794872
+2016-08-24 09:24:10,739 DEBUG: View 1 : 0.429487179487
+2016-08-24 09:24:10,775 DEBUG: View 2 : 0.608974358974
+2016-08-24 09:24:10,783 DEBUG: View 3 : 0.608974358974
+2016-08-24 09:24:10,843 DEBUG: Best view : RANSeq_
+2016-08-24 09:24:11,237 DEBUG: Start: Iteration 7
+2016-08-24 09:24:11,253 DEBUG: View 0 : 0.467948717949
+2016-08-24 09:24:11,261 DEBUG: View 1 : 0.570512820513
+2016-08-24 09:24:11,297 DEBUG: View 2 : 0.403846153846
+2016-08-24 09:24:11,305 DEBUG: View 3 : 0.487179487179
+2016-08-24 09:24:11,367 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:11,817 DEBUG: Start: Iteration 8
+2016-08-24 09:24:11,834 DEBUG: View 0 : 0.410256410256
+2016-08-24 09:24:11,841 DEBUG: View 1 : 0.435897435897
+2016-08-24 09:24:11,877 DEBUG: View 2 : 0.615384615385
+2016-08-24 09:24:11,885 DEBUG: View 3 : 0.570512820513
+2016-08-24 09:24:11,949 DEBUG: Best view : Clinic_
+2016-08-24 09:24:12,494 DEBUG: Start: Iteration 9
+2016-08-24 09:24:12,510 DEBUG: View 0 : 0.583333333333
+2016-08-24 09:24:12,518 DEBUG: View 1 : 0.602564102564
+2016-08-24 09:24:12,556 DEBUG: View 2 : 0.391025641026
+2016-08-24 09:24:12,563 DEBUG: View 3 : 0.461538461538
+2016-08-24 09:24:12,633 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:13,242 DEBUG: Start: Iteration 10
+2016-08-24 09:24:13,269 DEBUG: View 0 : 0.551282051282
+2016-08-24 09:24:13,278 DEBUG: View 1 : 0.647435897436
+2016-08-24 09:24:13,322 DEBUG: View 2 : 0.551282051282
+2016-08-24 09:24:13,331 DEBUG: View 3 : 0.602564102564
+2016-08-24 09:24:13,410 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:14,046 DEBUG: Start: Iteration 11
+2016-08-24 09:24:14,063 DEBUG: View 0 : 0.435897435897
+2016-08-24 09:24:14,070 DEBUG: View 1 : 0.455128205128
+2016-08-24 09:24:14,106 DEBUG: View 2 : 0.416666666667
+2016-08-24 09:24:14,114 DEBUG: View 3 : 0.532051282051
+2016-08-24 09:24:14,187 DEBUG: Best view : Clinic_
+2016-08-24 09:24:14,942 DEBUG: Start: Iteration 12
+2016-08-24 09:24:14,963 DEBUG: View 0 : 0.724358974359
+2016-08-24 09:24:14,972 DEBUG: View 1 : 0.775641025641
+2016-08-24 09:24:15,010 DEBUG: View 2 : 0.467948717949
+2016-08-24 09:24:15,019 DEBUG: View 3 : 0.487179487179
+2016-08-24 09:24:15,094 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:15,834 DEBUG: Start: Iteration 13
+2016-08-24 09:24:15,853 DEBUG: View 0 : 0.782051282051
+2016-08-24 09:24:15,861 DEBUG: View 1 : 0.480769230769
+2016-08-24 09:24:15,899 DEBUG: View 2 : 0.538461538462
+2016-08-24 09:24:15,907 DEBUG: View 3 : 0.423076923077
+2016-08-24 09:24:15,982 DEBUG: Best view : Methyl_
+2016-08-24 09:24:16,787 DEBUG: Start: Iteration 14
+2016-08-24 09:24:16,804 DEBUG: View 0 : 0.788461538462
+2016-08-24 09:24:16,812 DEBUG: View 1 : 0.641025641026
+2016-08-24 09:24:16,848 DEBUG: View 2 : 0.564102564103
+2016-08-24 09:24:16,856 DEBUG: View 3 : 0.615384615385
+2016-08-24 09:24:16,934 DEBUG: Best view : Methyl_
+2016-08-24 09:24:17,794 DEBUG: Start: Iteration 15
+2016-08-24 09:24:17,810 DEBUG: View 0 : 0.589743589744
+2016-08-24 09:24:17,818 DEBUG: View 1 : 0.519230769231
+2016-08-24 09:24:17,854 DEBUG: View 2 : 0.403846153846
+2016-08-24 09:24:17,861 DEBUG: View 3 : 0.570512820513
+2016-08-24 09:24:17,941 DEBUG: Best view : Methyl_
+2016-08-24 09:24:18,865 DEBUG: Start: Iteration 16
+2016-08-24 09:24:18,882 DEBUG: View 0 : 0.673076923077
+2016-08-24 09:24:18,890 DEBUG: View 1 : 0.634615384615
+2016-08-24 09:24:18,930 DEBUG: View 2 : 0.461538461538
+2016-08-24 09:24:18,938 DEBUG: View 3 : 0.416666666667
+2016-08-24 09:24:19,022 DEBUG: Best view : Methyl_
+2016-08-24 09:24:20,318 DEBUG: Start: Iteration 17
+2016-08-24 09:24:20,347 DEBUG: View 0 : 0.685897435897
+2016-08-24 09:24:20,361 DEBUG: View 1 : 0.403846153846
+2016-08-24 09:24:20,409 DEBUG: View 2 : 0.50641025641
+2016-08-24 09:24:20,418 DEBUG: View 3 : 0.666666666667
+2016-08-24 09:24:20,513 DEBUG: Best view : Clinic_
+2016-08-24 09:24:21,727 DEBUG: Start: Iteration 18
+2016-08-24 09:24:21,746 DEBUG: View 0 : 0.544871794872
+2016-08-24 09:24:21,755 DEBUG: View 1 : 0.467948717949
+2016-08-24 09:24:21,799 DEBUG: View 2 : 0.576923076923
+2016-08-24 09:24:21,809 DEBUG: View 3 : 0.455128205128
+2016-08-24 09:24:21,907 DEBUG: Best view : Methyl_
+2016-08-24 09:24:23,082 DEBUG: Start: Iteration 19
+2016-08-24 09:24:23,100 DEBUG: View 0 : 0.519230769231
+2016-08-24 09:24:23,109 DEBUG: View 1 : 0.339743589744
+2016-08-24 09:24:23,158 DEBUG: View 2 : 0.525641025641
+2016-08-24 09:24:23,167 DEBUG: View 3 : 0.525641025641
+2016-08-24 09:24:23,274 DEBUG: Best view : Methyl_
+2016-08-24 09:24:24,497 DEBUG: Start: Iteration 20
+2016-08-24 09:24:24,515 DEBUG: View 0 : 0.615384615385
+2016-08-24 09:24:24,523 DEBUG: View 1 : 0.50641025641
+2016-08-24 09:24:24,571 DEBUG: View 2 : 0.384615384615
+2016-08-24 09:24:24,579 DEBUG: View 3 : 0.512820512821
+2016-08-24 09:24:24,674 DEBUG: Best view : Methyl_
+2016-08-24 09:24:25,966 DEBUG: Start: Iteration 21
+2016-08-24 09:24:25,984 DEBUG: View 0 : 0.391025641026
+2016-08-24 09:24:25,992 DEBUG: View 1 : 0.615384615385
+2016-08-24 09:24:26,030 DEBUG: View 2 : 0.480769230769
+2016-08-24 09:24:26,038 DEBUG: View 3 : 0.538461538462
+2016-08-24 09:24:26,133 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:27,438 DEBUG: Start: Iteration 22
+2016-08-24 09:24:27,455 DEBUG: View 0 : 0.358974358974
+2016-08-24 09:24:27,463 DEBUG: View 1 : 0.730769230769
+2016-08-24 09:24:27,499 DEBUG: View 2 : 0.557692307692
+2016-08-24 09:24:27,507 DEBUG: View 3 : 0.378205128205
+2016-08-24 09:24:27,603 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:29,071 DEBUG: Start: Iteration 23
+2016-08-24 09:24:29,087 DEBUG: View 0 : 0.512820512821
+2016-08-24 09:24:29,095 DEBUG: View 1 : 0.371794871795
+2016-08-24 09:24:29,135 DEBUG: View 2 : 0.487179487179
+2016-08-24 09:24:29,143 DEBUG: View 3 : 0.455128205128
+2016-08-24 09:24:29,243 DEBUG: Best view : Methyl_
+2016-08-24 09:24:30,754 DEBUG: Start: Iteration 24
+2016-08-24 09:24:30,771 DEBUG: View 0 : 0.615384615385
+2016-08-24 09:24:30,779 DEBUG: View 1 : 0.698717948718
+2016-08-24 09:24:30,832 DEBUG: View 2 : 0.49358974359
+2016-08-24 09:24:30,848 DEBUG: View 3 : 0.583333333333
+2016-08-24 09:24:30,972 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:32,536 DEBUG: Start: Iteration 25
+2016-08-24 09:24:32,553 DEBUG: View 0 : 0.512820512821
+2016-08-24 09:24:32,561 DEBUG: View 1 : 0.461538461538
+2016-08-24 09:24:32,598 DEBUG: View 2 : 0.532051282051
+2016-08-24 09:24:32,609 DEBUG: View 3 : 0.512820512821
+2016-08-24 09:24:32,735 DEBUG: Best view : Methyl_
+2016-08-24 09:24:34,372 DEBUG: Start: Iteration 26
+2016-08-24 09:24:34,395 DEBUG: View 0 : 0.705128205128
+2016-08-24 09:24:34,404 DEBUG: View 1 : 0.442307692308
+2016-08-24 09:24:34,443 DEBUG: View 2 : 0.5
+2016-08-24 09:24:34,451 DEBUG: View 3 : 0.666666666667
+2016-08-24 09:24:34,558 DEBUG: Best view : Methyl_
+2016-08-24 09:24:36,187 DEBUG: Start: Iteration 27
+2016-08-24 09:24:36,206 DEBUG: View 0 : 0.525641025641
+2016-08-24 09:24:36,214 DEBUG: View 1 : 0.429487179487
+2016-08-24 09:24:36,252 DEBUG: View 2 : 0.467948717949
+2016-08-24 09:24:36,260 DEBUG: View 3 : 0.467948717949
+2016-08-24 09:24:36,370 DEBUG: Best view : Methyl_
+2016-08-24 09:24:38,001 DEBUG: Start: Iteration 28
+2016-08-24 09:24:38,017 DEBUG: View 0 : 0.608974358974
+2016-08-24 09:24:38,025 DEBUG: View 1 : 0.448717948718
+2016-08-24 09:24:38,061 DEBUG: View 2 : 0.589743589744
+2016-08-24 09:24:38,069 DEBUG: View 3 : 0.416666666667
+2016-08-24 09:24:38,177 DEBUG: Best view : Methyl_
+2016-08-24 09:24:39,928 DEBUG: Start: Iteration 29
+2016-08-24 09:24:39,944 DEBUG: View 0 : 0.403846153846
+2016-08-24 09:24:39,952 DEBUG: View 1 : 0.410256410256
+2016-08-24 09:24:39,989 DEBUG: View 2 : 0.538461538462
+2016-08-24 09:24:39,997 DEBUG: View 3 : 0.544871794872
+2016-08-24 09:24:40,108 DEBUG: Best view : Clinic_
+2016-08-24 09:24:41,868 DEBUG: Start: Iteration 30
+2016-08-24 09:24:41,885 DEBUG: View 0 : 0.692307692308
+2016-08-24 09:24:41,893 DEBUG: View 1 : 0.49358974359
+2016-08-24 09:24:41,929 DEBUG: View 2 : 0.423076923077
+2016-08-24 09:24:41,937 DEBUG: View 3 : 0.487179487179
+2016-08-24 09:24:42,050 DEBUG: Best view : Methyl_
+2016-08-24 09:24:44,013 DEBUG: Start: Iteration 31
+2016-08-24 09:24:44,030 DEBUG: View 0 : 0.442307692308
+2016-08-24 09:24:44,038 DEBUG: View 1 : 0.576923076923
+2016-08-24 09:24:44,074 DEBUG: View 2 : 0.442307692308
+2016-08-24 09:24:44,082 DEBUG: View 3 : 0.538461538462
+2016-08-24 09:24:44,197 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:46,115 DEBUG: Start: Iteration 32
+2016-08-24 09:24:46,140 DEBUG: View 0 : 0.448717948718
+2016-08-24 09:24:46,155 DEBUG: View 1 : 0.326923076923
+2016-08-24 09:24:46,202 DEBUG: View 2 : 0.512820512821
+2016-08-24 09:24:46,212 DEBUG: View 3 : 0.442307692308
+2016-08-24 09:24:46,350 DEBUG: Best view : RANSeq_
+2016-08-24 09:24:48,336 DEBUG: Start: Iteration 33
+2016-08-24 09:24:48,352 DEBUG: View 0 : 0.621794871795
+2016-08-24 09:24:48,360 DEBUG: View 1 : 0.50641025641
+2016-08-24 09:24:48,397 DEBUG: View 2 : 0.589743589744
+2016-08-24 09:24:48,405 DEBUG: View 3 : 0.429487179487
+2016-08-24 09:24:48,525 DEBUG: Best view : Methyl_
+2016-08-24 09:24:50,614 DEBUG: Start: Iteration 34
+2016-08-24 09:24:50,633 DEBUG: View 0 : 0.416666666667
+2016-08-24 09:24:50,642 DEBUG: View 1 : 0.391025641026
+2016-08-24 09:24:50,684 DEBUG: View 2 : 0.5
+2016-08-24 09:24:50,693 DEBUG: View 3 : 0.423076923077
+2016-08-24 09:24:50,835 DEBUG: Best view : RANSeq_
+2016-08-24 09:24:53,102 DEBUG: Start: Iteration 35
+2016-08-24 09:24:53,119 DEBUG: View 0 : 0.564102564103
+2016-08-24 09:24:53,126 DEBUG: View 1 : 0.589743589744
+2016-08-24 09:24:53,163 DEBUG: View 2 : 0.391025641026
+2016-08-24 09:24:53,171 DEBUG: View 3 : 0.519230769231
+2016-08-24 09:24:53,313 DEBUG: Best view : Methyl_
+2016-08-24 09:24:55,605 DEBUG: Start: Iteration 36
+2016-08-24 09:24:55,622 DEBUG: View 0 : 0.448717948718
+2016-08-24 09:24:55,630 DEBUG: View 1 : 0.653846153846
+2016-08-24 09:24:55,667 DEBUG: View 2 : 0.589743589744
+2016-08-24 09:24:55,675 DEBUG: View 3 : 0.397435897436
+2016-08-24 09:24:55,810 DEBUG: Best view : MiRNA__
+2016-08-24 09:24:58,037 DEBUG: Start: Iteration 37
+2016-08-24 09:24:58,053 DEBUG: View 0 : 0.461538461538
+2016-08-24 09:24:58,061 DEBUG: View 1 : 0.660256410256
+2016-08-24 09:24:58,098 DEBUG: View 2 : 0.5
+2016-08-24 09:24:58,105 DEBUG: View 3 : 0.525641025641
+2016-08-24 09:24:58,235 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:00,477 DEBUG: Start: Iteration 38
+2016-08-24 09:25:00,494 DEBUG: View 0 : 0.525641025641
+2016-08-24 09:25:00,502 DEBUG: View 1 : 0.49358974359
+2016-08-24 09:25:00,540 DEBUG: View 2 : 0.551282051282
+2016-08-24 09:25:00,548 DEBUG: View 3 : 0.519230769231
+2016-08-24 09:25:00,684 DEBUG: Best view : Methyl_
+2016-08-24 09:25:02,984 DEBUG: Start: Iteration 39
+2016-08-24 09:25:03,001 DEBUG: View 0 : 0.532051282051
+2016-08-24 09:25:03,008 DEBUG: View 1 : 0.641025641026
+2016-08-24 09:25:03,045 DEBUG: View 2 : 0.576923076923
+2016-08-24 09:25:03,053 DEBUG: View 3 : 0.647435897436
+2016-08-24 09:25:03,187 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:05,555 DEBUG: Start: Iteration 40
+2016-08-24 09:25:05,571 DEBUG: View 0 : 0.442307692308
+2016-08-24 09:25:05,579 DEBUG: View 1 : 0.634615384615
+2016-08-24 09:25:05,616 DEBUG: View 2 : 0.512820512821
+2016-08-24 09:25:05,624 DEBUG: View 3 : 0.532051282051
+2016-08-24 09:25:05,761 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:08,173 DEBUG: Start: Iteration 41
+2016-08-24 09:25:08,189 DEBUG: View 0 : 0.576923076923
+2016-08-24 09:25:08,197 DEBUG: View 1 : 0.692307692308
+2016-08-24 09:25:08,233 DEBUG: View 2 : 0.615384615385
+2016-08-24 09:25:08,241 DEBUG: View 3 : 0.589743589744
+2016-08-24 09:25:08,380 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:10,856 DEBUG: Start: Iteration 42
+2016-08-24 09:25:10,873 DEBUG: View 0 : 0.410256410256
+2016-08-24 09:25:10,881 DEBUG: View 1 : 0.384615384615
+2016-08-24 09:25:10,918 DEBUG: View 2 : 0.621794871795
+2016-08-24 09:25:10,926 DEBUG: View 3 : 0.564102564103
+2016-08-24 09:25:11,067 DEBUG: Best view : RANSeq_
+2016-08-24 09:25:13,607 DEBUG: Start: Iteration 43
+2016-08-24 09:25:13,623 DEBUG: View 0 : 0.608974358974
+2016-08-24 09:25:13,631 DEBUG: View 1 : 0.711538461538
+2016-08-24 09:25:13,668 DEBUG: View 2 : 0.557692307692
+2016-08-24 09:25:13,675 DEBUG: View 3 : 0.589743589744
+2016-08-24 09:25:13,817 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:16,417 DEBUG: Start: Iteration 44
+2016-08-24 09:25:16,434 DEBUG: View 0 : 0.423076923077
+2016-08-24 09:25:16,442 DEBUG: View 1 : 0.641025641026
+2016-08-24 09:25:16,478 DEBUG: View 2 : 0.538461538462
+2016-08-24 09:25:16,486 DEBUG: View 3 : 0.608974358974
+2016-08-24 09:25:16,632 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:19,287 DEBUG: Start: Iteration 45
+2016-08-24 09:25:19,303 DEBUG: View 0 : 0.49358974359
+2016-08-24 09:25:19,311 DEBUG: View 1 : 0.628205128205
+2016-08-24 09:25:19,348 DEBUG: View 2 : 0.519230769231
+2016-08-24 09:25:19,356 DEBUG: View 3 : 0.544871794872
+2016-08-24 09:25:19,504 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:22,218 DEBUG: Start: Iteration 46
+2016-08-24 09:25:22,235 DEBUG: View 0 : 0.525641025641
+2016-08-24 09:25:22,243 DEBUG: View 1 : 0.423076923077
+2016-08-24 09:25:22,280 DEBUG: View 2 : 0.544871794872
+2016-08-24 09:25:22,287 DEBUG: View 3 : 0.416666666667
+2016-08-24 09:25:22,437 DEBUG: Best view : Methyl_
+2016-08-24 09:25:25,212 DEBUG: Start: Iteration 47
+2016-08-24 09:25:25,228 DEBUG: View 0 : 0.378205128205
+2016-08-24 09:25:25,236 DEBUG: View 1 : 0.480769230769
+2016-08-24 09:25:25,273 DEBUG: View 2 : 0.583333333333
+2016-08-24 09:25:25,281 DEBUG: View 3 : 0.570512820513
+2016-08-24 09:25:25,434 DEBUG: Best view : Clinic_
+2016-08-24 09:25:28,262 DEBUG: Start: Iteration 48
+2016-08-24 09:25:28,279 DEBUG: View 0 : 0.525641025641
+2016-08-24 09:25:28,287 DEBUG: View 1 : 0.333333333333
+2016-08-24 09:25:28,323 DEBUG: View 2 : 0.544871794872
+2016-08-24 09:25:28,331 DEBUG: View 3 : 0.435897435897
+2016-08-24 09:25:28,487 DEBUG: Best view : RANSeq_
+2016-08-24 09:25:31,392 DEBUG: Start: Iteration 49
+2016-08-24 09:25:31,409 DEBUG: View 0 : 0.570512820513
+2016-08-24 09:25:31,416 DEBUG: View 1 : 0.50641025641
+2016-08-24 09:25:31,453 DEBUG: View 2 : 0.474358974359
+2016-08-24 09:25:31,461 DEBUG: View 3 : 0.461538461538
+2016-08-24 09:25:31,616 DEBUG: Best view : Methyl_
+2016-08-24 09:25:34,579 DEBUG: Start: Iteration 50
+2016-08-24 09:25:34,596 DEBUG: View 0 : 0.628205128205
+2016-08-24 09:25:34,604 DEBUG: View 1 : 0.474358974359
+2016-08-24 09:25:34,640 DEBUG: View 2 : 0.576923076923
+2016-08-24 09:25:34,648 DEBUG: View 3 : 0.519230769231
+2016-08-24 09:25:34,807 DEBUG: Best view : Methyl_
+2016-08-24 09:25:37,851 DEBUG: Start: Iteration 51
+2016-08-24 09:25:37,868 DEBUG: View 0 : 0.525641025641
+2016-08-24 09:25:37,876 DEBUG: View 1 : 0.49358974359
+2016-08-24 09:25:37,912 DEBUG: View 2 : 0.50641025641
+2016-08-24 09:25:37,920 DEBUG: View 3 : 0.397435897436
+2016-08-24 09:25:38,082 DEBUG: Best view : Methyl_
+2016-08-24 09:25:41,390 DEBUG: Start: Iteration 52
+2016-08-24 09:25:41,409 DEBUG: View 0 : 0.397435897436
+2016-08-24 09:25:41,417 DEBUG: View 1 : 0.634615384615
+2016-08-24 09:25:41,454 DEBUG: View 2 : 0.532051282051
+2016-08-24 09:25:41,462 DEBUG: View 3 : 0.416666666667
+2016-08-24 09:25:41,625 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:44,792 INFO: Start: Classification
+2016-08-24 09:25:52,398 INFO: Done: Fold number 1
+2016-08-24 09:25:52,398 INFO: Start: Fold number 2
+2016-08-24 09:25:54,031 DEBUG: Start: Iteration 1
+2016-08-24 09:25:54,047 DEBUG: View 0 : 0.62962962963
+2016-08-24 09:25:54,055 DEBUG: View 1 : 0.666666666667
+2016-08-24 09:25:54,093 DEBUG: View 2 : 0.623456790123
+2016-08-24 09:25:54,101 DEBUG: View 3 : 0.37037037037
+2016-08-24 09:25:54,143 DEBUG: Best view : Clinic_
+2016-08-24 09:25:54,215 DEBUG: Start: Iteration 2
+2016-08-24 09:25:54,233 DEBUG: View 0 : 0.530864197531
+2016-08-24 09:25:54,241 DEBUG: View 1 : 0.277777777778
+2016-08-24 09:25:54,279 DEBUG: View 2 : 0.41975308642
+2016-08-24 09:25:54,287 DEBUG: View 3 : 0.561728395062
+2016-08-24 09:25:54,340 DEBUG: Best view : Clinic_
+2016-08-24 09:25:54,473 DEBUG: Start: Iteration 3
+2016-08-24 09:25:54,491 DEBUG: View 0 : 0.506172839506
+2016-08-24 09:25:54,502 DEBUG: View 1 : 0.592592592593
+2016-08-24 09:25:54,543 DEBUG: View 2 : 0.549382716049
+2016-08-24 09:25:54,551 DEBUG: View 3 : 0.450617283951
+2016-08-24 09:25:54,607 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:54,799 DEBUG: Start: Iteration 4
+2016-08-24 09:25:54,817 DEBUG: View 0 : 0.469135802469
+2016-08-24 09:25:54,825 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:25:54,865 DEBUG: View 2 : 0.487654320988
+2016-08-24 09:25:54,873 DEBUG: View 3 : 0.382716049383
+2016-08-24 09:25:54,931 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:55,184 DEBUG: Start: Iteration 5
+2016-08-24 09:25:55,202 DEBUG: View 0 : 0.506172839506
+2016-08-24 09:25:55,211 DEBUG: View 1 : 0.716049382716
+2016-08-24 09:25:55,249 DEBUG: View 2 : 0.469135802469
+2016-08-24 09:25:55,257 DEBUG: View 3 : 0.623456790123
+2016-08-24 09:25:55,325 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:55,645 DEBUG: Start: Iteration 6
+2016-08-24 09:25:55,663 DEBUG: View 0 : 0.388888888889
+2016-08-24 09:25:55,671 DEBUG: View 1 : 0.771604938272
+2016-08-24 09:25:55,709 DEBUG: View 2 : 0.598765432099
+2016-08-24 09:25:55,717 DEBUG: View 3 : 0.524691358025
+2016-08-24 09:25:55,779 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:56,151 DEBUG: Start: Iteration 7
+2016-08-24 09:25:56,168 DEBUG: View 0 : 0.524691358025
+2016-08-24 09:25:56,176 DEBUG: View 1 : 0.641975308642
+2016-08-24 09:25:56,214 DEBUG: View 2 : 0.506172839506
+2016-08-24 09:25:56,222 DEBUG: View 3 : 0.537037037037
+2016-08-24 09:25:56,288 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:56,721 DEBUG: Start: Iteration 8
+2016-08-24 09:25:56,738 DEBUG: View 0 : 0.413580246914
+2016-08-24 09:25:56,747 DEBUG: View 1 : 0.524691358025
+2016-08-24 09:25:56,785 DEBUG: View 2 : 0.586419753086
+2016-08-24 09:25:56,793 DEBUG: View 3 : 0.407407407407
+2016-08-24 09:25:56,862 DEBUG: Best view : RANSeq_
+2016-08-24 09:25:57,369 DEBUG: Start: Iteration 9
+2016-08-24 09:25:57,386 DEBUG: View 0 : 0.444444444444
+2016-08-24 09:25:57,394 DEBUG: View 1 : 0.604938271605
+2016-08-24 09:25:57,431 DEBUG: View 2 : 0.444444444444
+2016-08-24 09:25:57,439 DEBUG: View 3 : 0.481481481481
+2016-08-24 09:25:57,507 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:58,072 DEBUG: Start: Iteration 10
+2016-08-24 09:25:58,089 DEBUG: View 0 : 0.382716049383
+2016-08-24 09:25:58,097 DEBUG: View 1 : 0.623456790123
+2016-08-24 09:25:58,134 DEBUG: View 2 : 0.617283950617
+2016-08-24 09:25:58,142 DEBUG: View 3 : 0.41975308642
+2016-08-24 09:25:58,213 DEBUG: Best view : MiRNA__
+2016-08-24 09:25:58,839 DEBUG: Start: Iteration 11
+2016-08-24 09:25:58,856 DEBUG: View 0 : 0.506172839506
+2016-08-24 09:25:58,864 DEBUG: View 1 : 0.487654320988
+2016-08-24 09:25:58,901 DEBUG: View 2 : 0.530864197531
+2016-08-24 09:25:58,909 DEBUG: View 3 : 0.407407407407
+2016-08-24 09:25:58,983 DEBUG: Best view : RANSeq_
+2016-08-24 09:25:59,688 DEBUG: Start: Iteration 12
+2016-08-24 09:25:59,705 DEBUG: View 0 : 0.518518518519
+2016-08-24 09:25:59,714 DEBUG: View 1 : 0.543209876543
+2016-08-24 09:25:59,751 DEBUG: View 2 : 0.530864197531
+2016-08-24 09:25:59,759 DEBUG: View 3 : 0.469135802469
+2016-08-24 09:25:59,835 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:00,606 DEBUG: Start: Iteration 13
+2016-08-24 09:26:00,623 DEBUG: View 0 : 0.487654320988
+2016-08-24 09:26:00,631 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:26:00,669 DEBUG: View 2 : 0.413580246914
+2016-08-24 09:26:00,676 DEBUG: View 3 : 0.530864197531
+2016-08-24 09:26:00,756 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:01,578 DEBUG: Start: Iteration 14
+2016-08-24 09:26:01,595 DEBUG: View 0 : 0.561728395062
+2016-08-24 09:26:01,603 DEBUG: View 1 : 0.555555555556
+2016-08-24 09:26:01,640 DEBUG: View 2 : 0.537037037037
+2016-08-24 09:26:01,648 DEBUG: View 3 : 0.376543209877
+2016-08-24 09:26:01,729 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:02,647 DEBUG: Start: Iteration 15
+2016-08-24 09:26:02,664 DEBUG: View 0 : 0.444444444444
+2016-08-24 09:26:02,672 DEBUG: View 1 : 0.364197530864
+2016-08-24 09:26:02,709 DEBUG: View 2 : 0.450617283951
+2016-08-24 09:26:02,717 DEBUG: View 3 : 0.561728395062
+2016-08-24 09:26:02,800 DEBUG: Best view : Clinic_
+2016-08-24 09:26:03,734 DEBUG: Start: Iteration 16
+2016-08-24 09:26:03,751 DEBUG: View 0 : 0.604938271605
+2016-08-24 09:26:03,759 DEBUG: View 1 : 0.666666666667
+2016-08-24 09:26:03,796 DEBUG: View 2 : 0.530864197531
+2016-08-24 09:26:03,804 DEBUG: View 3 : 0.611111111111
+2016-08-24 09:26:03,888 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:04,879 DEBUG: Start: Iteration 17
+2016-08-24 09:26:04,896 DEBUG: View 0 : 0.561728395062
+2016-08-24 09:26:04,904 DEBUG: View 1 : 0.641975308642
+2016-08-24 09:26:04,941 DEBUG: View 2 : 0.450617283951
+2016-08-24 09:26:04,948 DEBUG: View 3 : 0.62962962963
+2016-08-24 09:26:05,035 DEBUG: Best view : Clinic_
+2016-08-24 09:26:06,079 DEBUG: Start: Iteration 18
+2016-08-24 09:26:06,096 DEBUG: View 0 : 0.438271604938
+2016-08-24 09:26:06,104 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:26:06,141 DEBUG: View 2 : 0.493827160494
+2016-08-24 09:26:06,149 DEBUG: View 3 : 0.524691358025
+2016-08-24 09:26:06,238 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:07,352 DEBUG: Start: Iteration 19
+2016-08-24 09:26:07,369 DEBUG: View 0 : 0.512345679012
+2016-08-24 09:26:07,377 DEBUG: View 1 : 0.611111111111
+2016-08-24 09:26:07,415 DEBUG: View 2 : 0.617283950617
+2016-08-24 09:26:07,423 DEBUG: View 3 : 0.574074074074
+2016-08-24 09:26:07,517 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:08,688 DEBUG: Start: Iteration 20
+2016-08-24 09:26:08,705 DEBUG: View 0 : 0.407407407407
+2016-08-24 09:26:08,713 DEBUG: View 1 : 0.62962962963
+2016-08-24 09:26:08,751 DEBUG: View 2 : 0.549382716049
+2016-08-24 09:26:08,759 DEBUG: View 3 : 0.493827160494
+2016-08-24 09:26:08,855 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:10,080 DEBUG: Start: Iteration 21
+2016-08-24 09:26:10,097 DEBUG: View 0 : 0.561728395062
+2016-08-24 09:26:10,105 DEBUG: View 1 : 0.672839506173
+2016-08-24 09:26:10,142 DEBUG: View 2 : 0.648148148148
+2016-08-24 09:26:10,150 DEBUG: View 3 : 0.438271604938
+2016-08-24 09:26:10,246 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:11,549 DEBUG: Start: Iteration 22
+2016-08-24 09:26:11,566 DEBUG: View 0 : 0.549382716049
+2016-08-24 09:26:11,574 DEBUG: View 1 : 0.586419753086
+2016-08-24 09:26:11,612 DEBUG: View 2 : 0.450617283951
+2016-08-24 09:26:11,620 DEBUG: View 3 : 0.561728395062
+2016-08-24 09:26:11,718 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:13,055 DEBUG: Start: Iteration 23
+2016-08-24 09:26:13,072 DEBUG: View 0 : 0.592592592593
+2016-08-24 09:26:13,080 DEBUG: View 1 : 0.666666666667
+2016-08-24 09:26:13,117 DEBUG: View 2 : 0.62962962963
+2016-08-24 09:26:13,125 DEBUG: View 3 : 0.586419753086
+2016-08-24 09:26:13,226 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:14,621 DEBUG: Start: Iteration 24
+2016-08-24 09:26:14,638 DEBUG: View 0 : 0.425925925926
+2016-08-24 09:26:14,646 DEBUG: View 1 : 0.376543209877
+2016-08-24 09:26:14,684 DEBUG: View 2 : 0.475308641975
+2016-08-24 09:26:14,691 DEBUG: View 3 : 0.413580246914
+2016-08-24 09:26:14,692 WARNING: All bad for iteration 23
+2016-08-24 09:26:14,795 DEBUG: Best view : RANSeq_
+2016-08-24 09:26:16,277 DEBUG: Start: Iteration 25
+2016-08-24 09:26:16,294 DEBUG: View 0 : 0.462962962963
+2016-08-24 09:26:16,302 DEBUG: View 1 : 0.716049382716
+2016-08-24 09:26:16,339 DEBUG: View 2 : 0.530864197531
+2016-08-24 09:26:16,347 DEBUG: View 3 : 0.401234567901
+2016-08-24 09:26:16,452 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:18,023 DEBUG: Start: Iteration 26
+2016-08-24 09:26:18,040 DEBUG: View 0 : 0.62962962963
+2016-08-24 09:26:18,048 DEBUG: View 1 : 0.567901234568
+2016-08-24 09:26:18,089 DEBUG: View 2 : 0.506172839506
+2016-08-24 09:26:18,098 DEBUG: View 3 : 0.567901234568
+2016-08-24 09:26:18,209 DEBUG: Best view : Methyl_
+2016-08-24 09:26:19,837 DEBUG: Start: Iteration 27
+2016-08-24 09:26:19,854 DEBUG: View 0 : 0.413580246914
+2016-08-24 09:26:19,862 DEBUG: View 1 : 0.672839506173
+2016-08-24 09:26:19,900 DEBUG: View 2 : 0.364197530864
+2016-08-24 09:26:19,908 DEBUG: View 3 : 0.469135802469
+2016-08-24 09:26:20,019 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:21,774 DEBUG: Start: Iteration 28
+2016-08-24 09:26:21,791 DEBUG: View 0 : 0.555555555556
+2016-08-24 09:26:21,799 DEBUG: View 1 : 0.388888888889
+2016-08-24 09:26:21,837 DEBUG: View 2 : 0.530864197531
+2016-08-24 09:26:21,845 DEBUG: View 3 : 0.561728395062
+2016-08-24 09:26:21,962 DEBUG: Best view : Methyl_
+2016-08-24 09:26:23,703 DEBUG: Start: Iteration 29
+2016-08-24 09:26:23,720 DEBUG: View 0 : 0.493827160494
+2016-08-24 09:26:23,728 DEBUG: View 1 : 0.611111111111
+2016-08-24 09:26:23,765 DEBUG: View 2 : 0.617283950617
+2016-08-24 09:26:23,773 DEBUG: View 3 : 0.438271604938
+2016-08-24 09:26:23,890 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:25,713 DEBUG: Start: Iteration 30
+2016-08-24 09:26:25,730 DEBUG: View 0 : 0.432098765432
+2016-08-24 09:26:25,739 DEBUG: View 1 : 0.586419753086
+2016-08-24 09:26:25,776 DEBUG: View 2 : 0.604938271605
+2016-08-24 09:26:25,784 DEBUG: View 3 : 0.617283950617
+2016-08-24 09:26:25,904 DEBUG: Best view : Clinic_
+2016-08-24 09:26:27,986 DEBUG: Start: Iteration 31
+2016-08-24 09:26:28,004 DEBUG: View 0 : 0.623456790123
+2016-08-24 09:26:28,013 DEBUG: View 1 : 0.456790123457
+2016-08-24 09:26:28,051 DEBUG: View 2 : 0.506172839506
+2016-08-24 09:26:28,059 DEBUG: View 3 : 0.376543209877
+2016-08-24 09:26:28,180 DEBUG: Best view : Methyl_
+2016-08-24 09:26:30,112 DEBUG: Start: Iteration 32
+2016-08-24 09:26:30,129 DEBUG: View 0 : 0.456790123457
+2016-08-24 09:26:30,137 DEBUG: View 1 : 0.567901234568
+2016-08-24 09:26:30,175 DEBUG: View 2 : 0.382716049383
+2016-08-24 09:26:30,182 DEBUG: View 3 : 0.567901234568
+2016-08-24 09:26:30,305 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:32,285 DEBUG: Start: Iteration 33
+2016-08-24 09:26:32,302 DEBUG: View 0 : 0.512345679012
+2016-08-24 09:26:32,310 DEBUG: View 1 : 0.327160493827
+2016-08-24 09:26:32,347 DEBUG: View 2 : 0.592592592593
+2016-08-24 09:26:32,355 DEBUG: View 3 : 0.487654320988
+2016-08-24 09:26:32,483 DEBUG: Best view : RANSeq_
+2016-08-24 09:26:34,814 DEBUG: Start: Iteration 34
+2016-08-24 09:26:34,837 DEBUG: View 0 : 0.5
+2016-08-24 09:26:34,853 DEBUG: View 1 : 0.537037037037
+2016-08-24 09:26:34,913 DEBUG: View 2 : 0.487654320988
+2016-08-24 09:26:34,927 DEBUG: View 3 : 0.395061728395
+2016-08-24 09:26:35,074 DEBUG: Best view : MiRNA__
+2016-08-24 09:26:37,180 DEBUG: Start: Iteration 35
+2016-08-24 09:26:37,197 DEBUG: View 0 : 0.493827160494
+2016-08-24 09:26:37,205 DEBUG: View 1 : 0.493827160494
+2016-08-24 09:26:37,242 DEBUG: View 2 : 0.512345679012
+2016-08-24 09:26:37,250 DEBUG: View 3 : 0.641975308642
+2016-08-24 09:26:37,379 DEBUG: Best view : Clinic_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092640-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092640-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..1c9b53f08823be3ad9d40d9401da83eea1f96c6a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092640-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,50 @@
+2016-08-24 09:26:40,875 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:26:40,875 INFO: Info: Labels used: No, Yes
+2016-08-24 09:26:40,875 INFO: Info: Length of dataset:347
+2016-08-24 09:26:40,877 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:26:40,877 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:26:40,877 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:26:40,878 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:26:40,878 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:26:40,878 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:26:40,879 INFO: Done: Read Database Files
+2016-08-24 09:26:40,879 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:26:40,882 INFO: Done: Determine validation split
+2016-08-24 09:26:40,882 INFO: Start: Determine 2 folds
+2016-08-24 09:26:40,891 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:26:40,892 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:26:40,892 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:26:40,892 INFO: Done: Determine folds
+2016-08-24 09:26:40,892 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:26:40,892 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:26:40,892 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:26:48,203 DEBUG: 0.593198847262Poulet
+2016-08-24 09:26:48,203 DEBUG: 0.572910662824Poulet
+2016-08-24 09:26:48,203 DEBUG: 0.586167146974Poulet
+2016-08-24 09:26:48,203 DEBUG: 0.5134870317Poulet
+2016-08-24 09:26:48,203 DEBUG: 0.508933717579Poulet
+2016-08-24 09:26:48,203 DEBUG: 0.549682997118Poulet
+2016-08-24 09:26:48,204 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:26:48,204 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:26:50,116 DEBUG: 0.584495677233Poulet
+2016-08-24 09:26:50,117 DEBUG: 0.583342939481Poulet
+2016-08-24 09:26:50,117 DEBUG: 0.52288184438Poulet
+2016-08-24 09:26:50,117 DEBUG: 0.560691642651Poulet
+2016-08-24 09:26:50,117 DEBUG: 0.536657060519Poulet
+2016-08-24 09:26:50,117 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:26:50,117 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:27:07,105 DEBUG: 0.571469740634Poulet
+2016-08-24 09:27:07,105 DEBUG: 0.587665706052Poulet
+2016-08-24 09:27:07,105 DEBUG: 0.551527377522Poulet
+2016-08-24 09:27:07,105 DEBUG: 0.55469740634Poulet
+2016-08-24 09:27:07,105 DEBUG: 0.508760806916Poulet
+2016-08-24 09:27:07,105 DEBUG: 0.507262247839Poulet
+2016-08-24 09:27:07,106 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:27:07,107 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:27:08,919 DEBUG: 0.583227665706Poulet
+2016-08-24 09:27:08,919 DEBUG: 0.570489913545Poulet
+2016-08-24 09:27:08,919 DEBUG: 0.55976945245Poulet
+2016-08-24 09:27:08,919 DEBUG: 0.586570605187Poulet
+2016-08-24 09:27:08,919 DEBUG: 0.516195965418Poulet
+2016-08-24 09:27:08,919 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:27:08,920 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092735-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092735-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..a19abd196dec9008d67213022082119af465c39d
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-092735-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,650 @@
+2016-08-24 09:27:35,426 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:27:35,427 INFO: Info: Labels used: No, Yes
+2016-08-24 09:27:35,427 INFO: Info: Length of dataset:347
+2016-08-24 09:27:35,428 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:27:35,428 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:27:35,429 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:27:35,429 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:27:35,430 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:27:35,430 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:27:35,430 INFO: Done: Read Database Files
+2016-08-24 09:27:35,430 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:27:35,433 INFO: Done: Determine validation split
+2016-08-24 09:27:35,434 INFO: Start: Determine 2 folds
+2016-08-24 09:27:35,442 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:27:35,442 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:27:35,442 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:27:35,442 INFO: Done: Determine folds
+2016-08-24 09:27:35,442 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:27:35,442 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:27:35,442 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:27:42,729 DEBUG: 0.591873198847Poulet
+2016-08-24 09:27:42,729 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:27:42,730 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:27:44,640 DEBUG: 0.569740634006Poulet
+2016-08-24 09:27:44,640 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:27:44,641 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:28:01,306 DEBUG: 0.576945244957Poulet
+2016-08-24 09:28:01,306 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:28:01,307 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:28:03,058 DEBUG: 0.582305475504Poulet
+2016-08-24 09:28:03,058 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:28:03,058 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:28:40,826 DEBUG: 0.558962536023Poulet
+2016-08-24 09:28:40,827 DEBUG: 0.560518731988Poulet
+2016-08-24 09:28:40,827 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:28:40,827 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:28:40,827 INFO: Start: Fold number 1
+2016-08-24 09:28:42,410 DEBUG: Start: Iteration 1
+2016-08-24 09:28:42,426 DEBUG: View 0 : 0.602649006623
+2016-08-24 09:28:42,433 DEBUG: View 1 : 0.649006622517
+2016-08-24 09:28:42,460 DEBUG: View 2 : 0.602649006623
+2016-08-24 09:28:42,467 DEBUG: View 3 : 0.602649006623
+2016-08-24 09:28:42,507 DEBUG: Best view : Methyl_
+2016-08-24 09:28:42,579 DEBUG: Start: Iteration 2
+2016-08-24 09:28:42,596 DEBUG: View 0 : 0.549668874172
+2016-08-24 09:28:42,603 DEBUG: View 1 : 0.576158940397
+2016-08-24 09:28:42,639 DEBUG: View 2 : 0.529801324503
+2016-08-24 09:28:42,646 DEBUG: View 3 : 0.576158940397
+2016-08-24 09:28:42,689 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:42,816 DEBUG: Start: Iteration 3
+2016-08-24 09:28:42,832 DEBUG: View 0 : 0.470198675497
+2016-08-24 09:28:42,840 DEBUG: View 1 : 0.443708609272
+2016-08-24 09:28:42,875 DEBUG: View 2 : 0.543046357616
+2016-08-24 09:28:42,882 DEBUG: View 3 : 0.443708609272
+2016-08-24 09:28:42,933 DEBUG: Best view : RANSeq_
+2016-08-24 09:28:43,132 DEBUG: Start: Iteration 4
+2016-08-24 09:28:43,148 DEBUG: View 0 : 0.390728476821
+2016-08-24 09:28:43,155 DEBUG: View 1 : 0.715231788079
+2016-08-24 09:28:43,190 DEBUG: View 2 : 0.503311258278
+2016-08-24 09:28:43,198 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:28:43,250 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:43,503 DEBUG: Start: Iteration 5
+2016-08-24 09:28:43,520 DEBUG: View 0 : 0.483443708609
+2016-08-24 09:28:43,527 DEBUG: View 1 : 0.397350993377
+2016-08-24 09:28:43,563 DEBUG: View 2 : 0.602649006623
+2016-08-24 09:28:43,570 DEBUG: View 3 : 0.629139072848
+2016-08-24 09:28:43,624 DEBUG: Best view : Clinic_
+2016-08-24 09:28:43,933 DEBUG: Start: Iteration 6
+2016-08-24 09:28:43,949 DEBUG: View 0 : 0.675496688742
+2016-08-24 09:28:43,956 DEBUG: View 1 : 0.456953642384
+2016-08-24 09:28:43,992 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:28:43,999 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:28:44,056 DEBUG: Best view : Methyl_
+2016-08-24 09:28:44,423 DEBUG: Start: Iteration 7
+2016-08-24 09:28:44,439 DEBUG: View 0 : 0.602649006623
+2016-08-24 09:28:44,447 DEBUG: View 1 : 0.298013245033
+2016-08-24 09:28:44,482 DEBUG: View 2 : 0.602649006623
+2016-08-24 09:28:44,489 DEBUG: View 3 : 0.569536423841
+2016-08-24 09:28:44,547 DEBUG: Best view : RANSeq_
+2016-08-24 09:28:44,982 DEBUG: Start: Iteration 8
+2016-08-24 09:28:44,998 DEBUG: View 0 : 0.529801324503
+2016-08-24 09:28:45,005 DEBUG: View 1 : 0.390728476821
+2016-08-24 09:28:45,041 DEBUG: View 2 : 0.509933774834
+2016-08-24 09:28:45,048 DEBUG: View 3 : 0.509933774834
+2016-08-24 09:28:45,108 DEBUG: Best view : Methyl_
+2016-08-24 09:28:45,601 DEBUG: Start: Iteration 9
+2016-08-24 09:28:45,618 DEBUG: View 0 : 0.417218543046
+2016-08-24 09:28:45,625 DEBUG: View 1 : 0.609271523179
+2016-08-24 09:28:45,660 DEBUG: View 2 : 0.582781456954
+2016-08-24 09:28:45,668 DEBUG: View 3 : 0.476821192053
+2016-08-24 09:28:45,730 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:46,279 DEBUG: Start: Iteration 10
+2016-08-24 09:28:46,295 DEBUG: View 0 : 0.503311258278
+2016-08-24 09:28:46,303 DEBUG: View 1 : 0.635761589404
+2016-08-24 09:28:46,338 DEBUG: View 2 : 0.470198675497
+2016-08-24 09:28:46,345 DEBUG: View 3 : 0.58940397351
+2016-08-24 09:28:46,410 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:47,014 DEBUG: Start: Iteration 11
+2016-08-24 09:28:47,030 DEBUG: View 0 : 0.562913907285
+2016-08-24 09:28:47,038 DEBUG: View 1 : 0.582781456954
+2016-08-24 09:28:47,073 DEBUG: View 2 : 0.423841059603
+2016-08-24 09:28:47,080 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:28:47,147 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:47,805 DEBUG: Start: Iteration 12
+2016-08-24 09:28:47,821 DEBUG: View 0 : 0.529801324503
+2016-08-24 09:28:47,829 DEBUG: View 1 : 0.635761589404
+2016-08-24 09:28:47,864 DEBUG: View 2 : 0.437086092715
+2016-08-24 09:28:47,871 DEBUG: View 3 : 0.576158940397
+2016-08-24 09:28:47,940 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:48,655 DEBUG: Start: Iteration 13
+2016-08-24 09:28:48,671 DEBUG: View 0 : 0.483443708609
+2016-08-24 09:28:48,679 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:28:48,714 DEBUG: View 2 : 0.53642384106
+2016-08-24 09:28:48,721 DEBUG: View 3 : 0.430463576159
+2016-08-24 09:28:48,792 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:49,562 DEBUG: Start: Iteration 14
+2016-08-24 09:28:49,579 DEBUG: View 0 : 0.450331125828
+2016-08-24 09:28:49,586 DEBUG: View 1 : 0.443708609272
+2016-08-24 09:28:49,621 DEBUG: View 2 : 0.483443708609
+2016-08-24 09:28:49,628 DEBUG: View 3 : 0.423841059603
+2016-08-24 09:28:49,628 WARNING: All bad for iteration 13
+2016-08-24 09:28:49,703 DEBUG: Best view : RANSeq_
+2016-08-24 09:28:50,539 DEBUG: Start: Iteration 15
+2016-08-24 09:28:50,555 DEBUG: View 0 : 0.470198675497
+2016-08-24 09:28:50,563 DEBUG: View 1 : 0.615894039735
+2016-08-24 09:28:50,598 DEBUG: View 2 : 0.490066225166
+2016-08-24 09:28:50,605 DEBUG: View 3 : 0.569536423841
+2016-08-24 09:28:50,682 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:51,575 DEBUG: Start: Iteration 16
+2016-08-24 09:28:51,591 DEBUG: View 0 : 0.456953642384
+2016-08-24 09:28:51,598 DEBUG: View 1 : 0.430463576159
+2016-08-24 09:28:51,633 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:28:51,640 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:28:51,718 DEBUG: Best view : Clinic_
+2016-08-24 09:28:52,694 DEBUG: Start: Iteration 17
+2016-08-24 09:28:52,710 DEBUG: View 0 : 0.403973509934
+2016-08-24 09:28:52,717 DEBUG: View 1 : 0.370860927152
+2016-08-24 09:28:52,752 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:28:52,760 DEBUG: View 3 : 0.417218543046
+2016-08-24 09:28:52,760 WARNING: All bad for iteration 16
+2016-08-24 09:28:52,839 DEBUG: Best view : RANSeq_
+2016-08-24 09:28:53,853 DEBUG: Start: Iteration 18
+2016-08-24 09:28:53,869 DEBUG: View 0 : 0.437086092715
+2016-08-24 09:28:53,876 DEBUG: View 1 : 0.483443708609
+2016-08-24 09:28:53,911 DEBUG: View 2 : 0.622516556291
+2016-08-24 09:28:53,918 DEBUG: View 3 : 0.629139072848
+2016-08-24 09:28:54,002 DEBUG: Best view : Clinic_
+2016-08-24 09:28:55,105 DEBUG: Start: Iteration 19
+2016-08-24 09:28:55,121 DEBUG: View 0 : 0.615894039735
+2016-08-24 09:28:55,129 DEBUG: View 1 : 0.430463576159
+2016-08-24 09:28:55,164 DEBUG: View 2 : 0.46357615894
+2016-08-24 09:28:55,171 DEBUG: View 3 : 0.496688741722
+2016-08-24 09:28:55,255 DEBUG: Best view : Methyl_
+2016-08-24 09:28:56,383 DEBUG: Start: Iteration 20
+2016-08-24 09:28:56,399 DEBUG: View 0 : 0.503311258278
+2016-08-24 09:28:56,407 DEBUG: View 1 : 0.602649006623
+2016-08-24 09:28:56,442 DEBUG: View 2 : 0.576158940397
+2016-08-24 09:28:56,449 DEBUG: View 3 : 0.576158940397
+2016-08-24 09:28:56,535 DEBUG: Best view : MiRNA__
+2016-08-24 09:28:57,716 DEBUG: Start: Iteration 21
+2016-08-24 09:28:57,732 DEBUG: View 0 : 0.496688741722
+2016-08-24 09:28:57,739 DEBUG: View 1 : 0.46357615894
+2016-08-24 09:28:57,774 DEBUG: View 2 : 0.417218543046
+2016-08-24 09:28:57,781 DEBUG: View 3 : 0.569536423841
+2016-08-24 09:28:57,870 DEBUG: Best view : Clinic_
+2016-08-24 09:28:59,107 DEBUG: Start: Iteration 22
+2016-08-24 09:28:59,123 DEBUG: View 0 : 0.728476821192
+2016-08-24 09:28:59,130 DEBUG: View 1 : 0.350993377483
+2016-08-24 09:28:59,165 DEBUG: View 2 : 0.529801324503
+2016-08-24 09:28:59,172 DEBUG: View 3 : 0.437086092715
+2016-08-24 09:28:59,262 DEBUG: Best view : Methyl_
+2016-08-24 09:29:00,559 DEBUG: Start: Iteration 23
+2016-08-24 09:29:00,575 DEBUG: View 0 : 0.476821192053
+2016-08-24 09:29:00,583 DEBUG: View 1 : 0.609271523179
+2016-08-24 09:29:00,618 DEBUG: View 2 : 0.503311258278
+2016-08-24 09:29:00,625 DEBUG: View 3 : 0.496688741722
+2016-08-24 09:29:00,718 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:02,130 DEBUG: Start: Iteration 24
+2016-08-24 09:29:02,147 DEBUG: View 0 : 0.615894039735
+2016-08-24 09:29:02,155 DEBUG: View 1 : 0.397350993377
+2016-08-24 09:29:02,193 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:29:02,201 DEBUG: View 3 : 0.576158940397
+2016-08-24 09:29:02,307 DEBUG: Best view : Methyl_
+2016-08-24 09:29:03,725 DEBUG: Start: Iteration 25
+2016-08-24 09:29:03,741 DEBUG: View 0 : 0.443708609272
+2016-08-24 09:29:03,748 DEBUG: View 1 : 0.615894039735
+2016-08-24 09:29:03,783 DEBUG: View 2 : 0.443708609272
+2016-08-24 09:29:03,790 DEBUG: View 3 : 0.370860927152
+2016-08-24 09:29:03,888 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:05,358 DEBUG: Start: Iteration 26
+2016-08-24 09:29:05,374 DEBUG: View 0 : 0.615894039735
+2016-08-24 09:29:05,381 DEBUG: View 1 : 0.556291390728
+2016-08-24 09:29:05,417 DEBUG: View 2 : 0.556291390728
+2016-08-24 09:29:05,425 DEBUG: View 3 : 0.41059602649
+2016-08-24 09:29:05,526 DEBUG: Best view : Methyl_
+2016-08-24 09:29:07,057 DEBUG: Start: Iteration 27
+2016-08-24 09:29:07,073 DEBUG: View 0 : 0.423841059603
+2016-08-24 09:29:07,081 DEBUG: View 1 : 0.688741721854
+2016-08-24 09:29:07,116 DEBUG: View 2 : 0.509933774834
+2016-08-24 09:29:07,123 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:29:07,225 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:08,808 DEBUG: Start: Iteration 28
+2016-08-24 09:29:08,824 DEBUG: View 0 : 0.543046357616
+2016-08-24 09:29:08,832 DEBUG: View 1 : 0.675496688742
+2016-08-24 09:29:08,867 DEBUG: View 2 : 0.549668874172
+2016-08-24 09:29:08,874 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:29:08,979 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:10,621 DEBUG: Start: Iteration 29
+2016-08-24 09:29:10,637 DEBUG: View 0 : 0.53642384106
+2016-08-24 09:29:10,645 DEBUG: View 1 : 0.701986754967
+2016-08-24 09:29:10,680 DEBUG: View 2 : 0.496688741722
+2016-08-24 09:29:10,687 DEBUG: View 3 : 0.516556291391
+2016-08-24 09:29:10,794 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:12,491 DEBUG: Start: Iteration 30
+2016-08-24 09:29:12,507 DEBUG: View 0 : 0.483443708609
+2016-08-24 09:29:12,514 DEBUG: View 1 : 0.615894039735
+2016-08-24 09:29:12,550 DEBUG: View 2 : 0.390728476821
+2016-08-24 09:29:12,557 DEBUG: View 3 : 0.509933774834
+2016-08-24 09:29:12,666 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:14,431 DEBUG: Start: Iteration 31
+2016-08-24 09:29:14,447 DEBUG: View 0 : 0.53642384106
+2016-08-24 09:29:14,454 DEBUG: View 1 : 0.58940397351
+2016-08-24 09:29:14,490 DEBUG: View 2 : 0.529801324503
+2016-08-24 09:29:14,497 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:29:14,607 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:16,428 DEBUG: Start: Iteration 32
+2016-08-24 09:29:16,445 DEBUG: View 0 : 0.523178807947
+2016-08-24 09:29:16,452 DEBUG: View 1 : 0.483443708609
+2016-08-24 09:29:16,488 DEBUG: View 2 : 0.470198675497
+2016-08-24 09:29:16,495 DEBUG: View 3 : 0.456953642384
+2016-08-24 09:29:16,608 DEBUG: Best view : Methyl_
+2016-08-24 09:29:18,508 DEBUG: Start: Iteration 33
+2016-08-24 09:29:18,524 DEBUG: View 0 : 0.582781456954
+2016-08-24 09:29:18,531 DEBUG: View 1 : 0.662251655629
+2016-08-24 09:29:18,568 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:29:18,575 DEBUG: View 3 : 0.523178807947
+2016-08-24 09:29:18,688 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:20,620 DEBUG: Start: Iteration 34
+2016-08-24 09:29:20,637 DEBUG: View 0 : 0.529801324503
+2016-08-24 09:29:20,644 DEBUG: View 1 : 0.450331125828
+2016-08-24 09:29:20,679 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:29:20,686 DEBUG: View 3 : 0.596026490066
+2016-08-24 09:29:20,802 DEBUG: Best view : Clinic_
+2016-08-24 09:29:22,810 DEBUG: Start: Iteration 35
+2016-08-24 09:29:22,827 DEBUG: View 0 : 0.523178807947
+2016-08-24 09:29:22,834 DEBUG: View 1 : 0.582781456954
+2016-08-24 09:29:22,872 DEBUG: View 2 : 0.668874172185
+2016-08-24 09:29:22,880 DEBUG: View 3 : 0.58940397351
+2016-08-24 09:29:23,000 DEBUG: Best view : RANSeq_
+2016-08-24 09:29:25,109 DEBUG: Start: Iteration 36
+2016-08-24 09:29:25,125 DEBUG: View 0 : 0.46357615894
+2016-08-24 09:29:25,133 DEBUG: View 1 : 0.390728476821
+2016-08-24 09:29:25,170 DEBUG: View 2 : 0.384105960265
+2016-08-24 09:29:25,178 DEBUG: View 3 : 0.53642384106
+2016-08-24 09:29:25,307 DEBUG: Best view : Clinic_
+2016-08-24 09:29:27,522 DEBUG: Start: Iteration 37
+2016-08-24 09:29:27,538 DEBUG: View 0 : 0.635761589404
+2016-08-24 09:29:27,545 DEBUG: View 1 : 0.476821192053
+2016-08-24 09:29:27,580 DEBUG: View 2 : 0.509933774834
+2016-08-24 09:29:27,588 DEBUG: View 3 : 0.523178807947
+2016-08-24 09:29:27,714 DEBUG: Best view : Methyl_
+2016-08-24 09:29:29,889 DEBUG: Start: Iteration 38
+2016-08-24 09:29:29,905 DEBUG: View 0 : 0.569536423841
+2016-08-24 09:29:29,912 DEBUG: View 1 : 0.64238410596
+2016-08-24 09:29:29,948 DEBUG: View 2 : 0.556291390728
+2016-08-24 09:29:29,955 DEBUG: View 3 : 0.423841059603
+2016-08-24 09:29:30,079 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:32,282 DEBUG: Start: Iteration 39
+2016-08-24 09:29:32,298 DEBUG: View 0 : 0.549668874172
+2016-08-24 09:29:32,305 DEBUG: View 1 : 0.562913907285
+2016-08-24 09:29:32,341 DEBUG: View 2 : 0.403973509934
+2016-08-24 09:29:32,348 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:29:32,473 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:34,735 DEBUG: Start: Iteration 40
+2016-08-24 09:29:34,751 DEBUG: View 0 : 0.569536423841
+2016-08-24 09:29:34,760 DEBUG: View 1 : 0.437086092715
+2016-08-24 09:29:34,797 DEBUG: View 2 : 0.46357615894
+2016-08-24 09:29:34,804 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:29:34,933 DEBUG: Best view : Methyl_
+2016-08-24 09:29:37,258 DEBUG: Start: Iteration 41
+2016-08-24 09:29:37,274 DEBUG: View 0 : 0.549668874172
+2016-08-24 09:29:37,281 DEBUG: View 1 : 0.708609271523
+2016-08-24 09:29:37,316 DEBUG: View 2 : 0.41059602649
+2016-08-24 09:29:37,323 DEBUG: View 3 : 0.437086092715
+2016-08-24 09:29:37,453 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:39,827 DEBUG: Start: Iteration 42
+2016-08-24 09:29:39,843 DEBUG: View 0 : 0.615894039735
+2016-08-24 09:29:39,850 DEBUG: View 1 : 0.549668874172
+2016-08-24 09:29:39,886 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:29:39,893 DEBUG: View 3 : 0.543046357616
+2016-08-24 09:29:40,025 DEBUG: Best view : Methyl_
+2016-08-24 09:29:42,592 DEBUG: Start: Iteration 43
+2016-08-24 09:29:42,611 DEBUG: View 0 : 0.602649006623
+2016-08-24 09:29:42,620 DEBUG: View 1 : 0.549668874172
+2016-08-24 09:29:42,664 DEBUG: View 2 : 0.450331125828
+2016-08-24 09:29:42,673 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:29:42,907 DEBUG: Best view : Methyl_
+2016-08-24 09:29:45,611 DEBUG: Start: Iteration 44
+2016-08-24 09:29:45,627 DEBUG: View 0 : 0.344370860927
+2016-08-24 09:29:45,635 DEBUG: View 1 : 0.582781456954
+2016-08-24 09:29:45,672 DEBUG: View 2 : 0.556291390728
+2016-08-24 09:29:45,679 DEBUG: View 3 : 0.450331125828
+2016-08-24 09:29:45,821 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:48,520 DEBUG: Start: Iteration 45
+2016-08-24 09:29:48,539 DEBUG: View 0 : 0.662251655629
+2016-08-24 09:29:48,548 DEBUG: View 1 : 0.596026490066
+2016-08-24 09:29:48,589 DEBUG: View 2 : 0.549668874172
+2016-08-24 09:29:48,597 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:29:48,760 DEBUG: Best view : Methyl_
+2016-08-24 09:29:51,441 DEBUG: Start: Iteration 46
+2016-08-24 09:29:51,457 DEBUG: View 0 : 0.523178807947
+2016-08-24 09:29:51,466 DEBUG: View 1 : 0.64238410596
+2016-08-24 09:29:51,502 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:29:51,510 DEBUG: View 3 : 0.430463576159
+2016-08-24 09:29:51,667 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:54,334 DEBUG: Start: Iteration 47
+2016-08-24 09:29:54,350 DEBUG: View 0 : 0.437086092715
+2016-08-24 09:29:54,358 DEBUG: View 1 : 0.53642384106
+2016-08-24 09:29:54,393 DEBUG: View 2 : 0.437086092715
+2016-08-24 09:29:54,401 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:29:54,544 DEBUG: Best view : MiRNA__
+2016-08-24 09:29:57,261 DEBUG: Start: Iteration 48
+2016-08-24 09:29:57,277 DEBUG: View 0 : 0.53642384106
+2016-08-24 09:29:57,285 DEBUG: View 1 : 0.569536423841
+2016-08-24 09:29:57,320 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:29:57,327 DEBUG: View 3 : 0.456953642384
+2016-08-24 09:29:57,473 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:00,260 DEBUG: Start: Iteration 49
+2016-08-24 09:30:00,276 DEBUG: View 0 : 0.509933774834
+2016-08-24 09:30:00,283 DEBUG: View 1 : 0.41059602649
+2016-08-24 09:30:00,319 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:30:00,326 DEBUG: View 3 : 0.496688741722
+2016-08-24 09:30:00,474 DEBUG: Best view : RANSeq_
+2016-08-24 09:30:03,315 DEBUG: Start: Iteration 50
+2016-08-24 09:30:03,331 DEBUG: View 0 : 0.569536423841
+2016-08-24 09:30:03,338 DEBUG: View 1 : 0.437086092715
+2016-08-24 09:30:03,373 DEBUG: View 2 : 0.430463576159
+2016-08-24 09:30:03,381 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:30:03,531 DEBUG: Best view : Methyl_
+2016-08-24 09:30:06,430 DEBUG: Start: Iteration 51
+2016-08-24 09:30:06,446 DEBUG: View 0 : 0.476821192053
+2016-08-24 09:30:06,453 DEBUG: View 1 : 0.602649006623
+2016-08-24 09:30:06,489 DEBUG: View 2 : 0.556291390728
+2016-08-24 09:30:06,496 DEBUG: View 3 : 0.609271523179
+2016-08-24 09:30:06,648 DEBUG: Best view : Clinic_
+2016-08-24 09:30:09,800 DEBUG: Start: Iteration 52
+2016-08-24 09:30:09,818 DEBUG: View 0 : 0.64238410596
+2016-08-24 09:30:09,826 DEBUG: View 1 : 0.490066225166
+2016-08-24 09:30:09,861 DEBUG: View 2 : 0.423841059603
+2016-08-24 09:30:09,868 DEBUG: View 3 : 0.470198675497
+2016-08-24 09:30:10,026 DEBUG: Best view : Methyl_
+2016-08-24 09:30:13,052 INFO: Start: Classification
+2016-08-24 09:30:20,660 INFO: Done: Fold number 1
+2016-08-24 09:30:20,660 INFO: Start: Fold number 2
+2016-08-24 09:30:22,264 DEBUG: Start: Iteration 1
+2016-08-24 09:30:22,279 DEBUG: View 0 : 0.62962962963
+2016-08-24 09:30:22,287 DEBUG: View 1 : 0.62962962963
+2016-08-24 09:30:22,315 DEBUG: View 2 : 0.62962962963
+2016-08-24 09:30:22,323 DEBUG: View 3 : 0.62962962963
+2016-08-24 09:30:22,364 DEBUG: Best view : Methyl_
+2016-08-24 09:30:22,443 DEBUG: Start: Iteration 2
+2016-08-24 09:30:22,461 DEBUG: View 0 : 0.432098765432
+2016-08-24 09:30:22,468 DEBUG: View 1 : 0.345679012346
+2016-08-24 09:30:22,506 DEBUG: View 2 : 0.37037037037
+2016-08-24 09:30:22,514 DEBUG: View 3 : 0.598765432099
+2016-08-24 09:30:22,560 DEBUG: Best view : Clinic_
+2016-08-24 09:30:22,701 DEBUG: Start: Iteration 3
+2016-08-24 09:30:22,718 DEBUG: View 0 : 0.481481481481
+2016-08-24 09:30:22,726 DEBUG: View 1 : 0.425925925926
+2016-08-24 09:30:22,764 DEBUG: View 2 : 0.555555555556
+2016-08-24 09:30:22,772 DEBUG: View 3 : 0.444444444444
+2016-08-24 09:30:22,827 DEBUG: Best view : RANSeq_
+2016-08-24 09:30:23,047 DEBUG: Start: Iteration 4
+2016-08-24 09:30:23,064 DEBUG: View 0 : 0.635802469136
+2016-08-24 09:30:23,072 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:30:23,109 DEBUG: View 2 : 0.450617283951
+2016-08-24 09:30:23,117 DEBUG: View 3 : 0.598765432099
+2016-08-24 09:30:23,174 DEBUG: Best view : Methyl_
+2016-08-24 09:30:23,451 DEBUG: Start: Iteration 5
+2016-08-24 09:30:23,468 DEBUG: View 0 : 0.462962962963
+2016-08-24 09:30:23,476 DEBUG: View 1 : 0.364197530864
+2016-08-24 09:30:23,513 DEBUG: View 2 : 0.469135802469
+2016-08-24 09:30:23,521 DEBUG: View 3 : 0.524691358025
+2016-08-24 09:30:23,579 DEBUG: Best view : Clinic_
+2016-08-24 09:30:23,913 DEBUG: Start: Iteration 6
+2016-08-24 09:30:23,929 DEBUG: View 0 : 0.592592592593
+2016-08-24 09:30:23,937 DEBUG: View 1 : 0.666666666667
+2016-08-24 09:30:23,974 DEBUG: View 2 : 0.493827160494
+2016-08-24 09:30:23,981 DEBUG: View 3 : 0.549382716049
+2016-08-24 09:30:24,042 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:24,446 DEBUG: Start: Iteration 7
+2016-08-24 09:30:24,463 DEBUG: View 0 : 0.413580246914
+2016-08-24 09:30:24,471 DEBUG: View 1 : 0.450617283951
+2016-08-24 09:30:24,509 DEBUG: View 2 : 0.432098765432
+2016-08-24 09:30:24,517 DEBUG: View 3 : 0.401234567901
+2016-08-24 09:30:24,517 WARNING: All bad for iteration 6
+2016-08-24 09:30:24,581 DEBUG: Best view : Clinic_
+2016-08-24 09:30:25,033 DEBUG: Start: Iteration 8
+2016-08-24 09:30:25,050 DEBUG: View 0 : 0.413580246914
+2016-08-24 09:30:25,058 DEBUG: View 1 : 0.648148148148
+2016-08-24 09:30:25,095 DEBUG: View 2 : 0.598765432099
+2016-08-24 09:30:25,102 DEBUG: View 3 : 0.549382716049
+2016-08-24 09:30:25,168 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:25,678 DEBUG: Start: Iteration 9
+2016-08-24 09:30:25,695 DEBUG: View 0 : 0.549382716049
+2016-08-24 09:30:25,703 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:30:25,740 DEBUG: View 2 : 0.567901234568
+2016-08-24 09:30:25,748 DEBUG: View 3 : 0.530864197531
+2016-08-24 09:30:25,815 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:26,384 DEBUG: Start: Iteration 10
+2016-08-24 09:30:26,401 DEBUG: View 0 : 0.716049382716
+2016-08-24 09:30:26,409 DEBUG: View 1 : 0.524691358025
+2016-08-24 09:30:26,445 DEBUG: View 2 : 0.444444444444
+2016-08-24 09:30:26,453 DEBUG: View 3 : 0.395061728395
+2016-08-24 09:30:26,522 DEBUG: Best view : Methyl_
+2016-08-24 09:30:27,154 DEBUG: Start: Iteration 11
+2016-08-24 09:30:27,171 DEBUG: View 0 : 0.407407407407
+2016-08-24 09:30:27,179 DEBUG: View 1 : 0.506172839506
+2016-08-24 09:30:27,216 DEBUG: View 2 : 0.469135802469
+2016-08-24 09:30:27,223 DEBUG: View 3 : 0.506172839506
+2016-08-24 09:30:27,295 DEBUG: Best view : Clinic_
+2016-08-24 09:30:27,985 DEBUG: Start: Iteration 12
+2016-08-24 09:30:28,001 DEBUG: View 0 : 0.524691358025
+2016-08-24 09:30:28,009 DEBUG: View 1 : 0.586419753086
+2016-08-24 09:30:28,046 DEBUG: View 2 : 0.543209876543
+2016-08-24 09:30:28,054 DEBUG: View 3 : 0.617283950617
+2016-08-24 09:30:28,128 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:28,887 DEBUG: Start: Iteration 13
+2016-08-24 09:30:28,904 DEBUG: View 0 : 0.567901234568
+2016-08-24 09:30:28,911 DEBUG: View 1 : 0.648148148148
+2016-08-24 09:30:28,948 DEBUG: View 2 : 0.432098765432
+2016-08-24 09:30:28,956 DEBUG: View 3 : 0.395061728395
+2016-08-24 09:30:29,034 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:29,843 DEBUG: Start: Iteration 14
+2016-08-24 09:30:29,860 DEBUG: View 0 : 0.5
+2016-08-24 09:30:29,868 DEBUG: View 1 : 0.716049382716
+2016-08-24 09:30:29,905 DEBUG: View 2 : 0.487654320988
+2016-08-24 09:30:29,912 DEBUG: View 3 : 0.537037037037
+2016-08-24 09:30:29,991 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:30,859 DEBUG: Start: Iteration 15
+2016-08-24 09:30:30,876 DEBUG: View 0 : 0.487654320988
+2016-08-24 09:30:30,884 DEBUG: View 1 : 0.70987654321
+2016-08-24 09:30:30,921 DEBUG: View 2 : 0.425925925926
+2016-08-24 09:30:30,929 DEBUG: View 3 : 0.462962962963
+2016-08-24 09:30:31,012 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:31,939 DEBUG: Start: Iteration 16
+2016-08-24 09:30:31,956 DEBUG: View 0 : 0.574074074074
+2016-08-24 09:30:31,963 DEBUG: View 1 : 0.364197530864
+2016-08-24 09:30:32,000 DEBUG: View 2 : 0.592592592593
+2016-08-24 09:30:32,008 DEBUG: View 3 : 0.444444444444
+2016-08-24 09:30:32,090 DEBUG: Best view : Methyl_
+2016-08-24 09:30:33,081 DEBUG: Start: Iteration 17
+2016-08-24 09:30:33,098 DEBUG: View 0 : 0.58024691358
+2016-08-24 09:30:33,106 DEBUG: View 1 : 0.413580246914
+2016-08-24 09:30:33,143 DEBUG: View 2 : 0.5
+2016-08-24 09:30:33,150 DEBUG: View 3 : 0.543209876543
+2016-08-24 09:30:33,236 DEBUG: Best view : Methyl_
+2016-08-24 09:30:34,291 DEBUG: Start: Iteration 18
+2016-08-24 09:30:34,307 DEBUG: View 0 : 0.530864197531
+2016-08-24 09:30:34,315 DEBUG: View 1 : 0.623456790123
+2016-08-24 09:30:34,352 DEBUG: View 2 : 0.444444444444
+2016-08-24 09:30:34,360 DEBUG: View 3 : 0.493827160494
+2016-08-24 09:30:34,448 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:35,560 DEBUG: Start: Iteration 19
+2016-08-24 09:30:35,576 DEBUG: View 0 : 0.41975308642
+2016-08-24 09:30:35,584 DEBUG: View 1 : 0.481481481481
+2016-08-24 09:30:35,621 DEBUG: View 2 : 0.432098765432
+2016-08-24 09:30:35,628 DEBUG: View 3 : 0.518518518519
+2016-08-24 09:30:35,719 DEBUG: Best view : Clinic_
+2016-08-24 09:30:36,890 DEBUG: Start: Iteration 20
+2016-08-24 09:30:36,907 DEBUG: View 0 : 0.518518518519
+2016-08-24 09:30:36,915 DEBUG: View 1 : 0.283950617284
+2016-08-24 09:30:36,952 DEBUG: View 2 : 0.58024691358
+2016-08-24 09:30:36,960 DEBUG: View 3 : 0.487654320988
+2016-08-24 09:30:37,053 DEBUG: Best view : RANSeq_
+2016-08-24 09:30:38,326 DEBUG: Start: Iteration 21
+2016-08-24 09:30:38,343 DEBUG: View 0 : 0.450617283951
+2016-08-24 09:30:38,351 DEBUG: View 1 : 0.623456790123
+2016-08-24 09:30:38,389 DEBUG: View 2 : 0.456790123457
+2016-08-24 09:30:38,397 DEBUG: View 3 : 0.462962962963
+2016-08-24 09:30:38,493 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:39,813 DEBUG: Start: Iteration 22
+2016-08-24 09:30:39,831 DEBUG: View 0 : 0.598765432099
+2016-08-24 09:30:39,839 DEBUG: View 1 : 0.345679012346
+2016-08-24 09:30:39,876 DEBUG: View 2 : 0.462962962963
+2016-08-24 09:30:39,884 DEBUG: View 3 : 0.604938271605
+2016-08-24 09:30:39,984 DEBUG: Best view : Methyl_
+2016-08-24 09:30:41,351 DEBUG: Start: Iteration 23
+2016-08-24 09:30:41,368 DEBUG: View 0 : 0.524691358025
+2016-08-24 09:30:41,375 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:30:41,413 DEBUG: View 2 : 0.635802469136
+2016-08-24 09:30:41,420 DEBUG: View 3 : 0.487654320988
+2016-08-24 09:30:41,519 DEBUG: Best view : RANSeq_
+2016-08-24 09:30:42,958 DEBUG: Start: Iteration 24
+2016-08-24 09:30:42,975 DEBUG: View 0 : 0.679012345679
+2016-08-24 09:30:42,983 DEBUG: View 1 : 0.401234567901
+2016-08-24 09:30:43,020 DEBUG: View 2 : 0.592592592593
+2016-08-24 09:30:43,027 DEBUG: View 3 : 0.456790123457
+2016-08-24 09:30:43,129 DEBUG: Best view : Methyl_
+2016-08-24 09:30:44,627 DEBUG: Start: Iteration 25
+2016-08-24 09:30:44,644 DEBUG: View 0 : 0.487654320988
+2016-08-24 09:30:44,652 DEBUG: View 1 : 0.654320987654
+2016-08-24 09:30:44,689 DEBUG: View 2 : 0.450617283951
+2016-08-24 09:30:44,696 DEBUG: View 3 : 0.58024691358
+2016-08-24 09:30:44,800 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:46,374 DEBUG: Start: Iteration 26
+2016-08-24 09:30:46,392 DEBUG: View 0 : 0.425925925926
+2016-08-24 09:30:46,400 DEBUG: View 1 : 0.376543209877
+2016-08-24 09:30:46,439 DEBUG: View 2 : 0.512345679012
+2016-08-24 09:30:46,446 DEBUG: View 3 : 0.475308641975
+2016-08-24 09:30:46,558 DEBUG: Best view : RANSeq_
+2016-08-24 09:30:48,255 DEBUG: Start: Iteration 27
+2016-08-24 09:30:48,272 DEBUG: View 0 : 0.586419753086
+2016-08-24 09:30:48,280 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:30:48,318 DEBUG: View 2 : 0.5
+2016-08-24 09:30:48,326 DEBUG: View 3 : 0.432098765432
+2016-08-24 09:30:48,434 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:50,179 DEBUG: Start: Iteration 28
+2016-08-24 09:30:50,196 DEBUG: View 0 : 0.524691358025
+2016-08-24 09:30:50,204 DEBUG: View 1 : 0.41975308642
+2016-08-24 09:30:50,242 DEBUG: View 2 : 0.481481481481
+2016-08-24 09:30:50,250 DEBUG: View 3 : 0.549382716049
+2016-08-24 09:30:50,361 DEBUG: Best view : Methyl_
+2016-08-24 09:30:52,134 DEBUG: Start: Iteration 29
+2016-08-24 09:30:52,151 DEBUG: View 0 : 0.438271604938
+2016-08-24 09:30:52,159 DEBUG: View 1 : 0.672839506173
+2016-08-24 09:30:52,197 DEBUG: View 2 : 0.617283950617
+2016-08-24 09:30:52,205 DEBUG: View 3 : 0.407407407407
+2016-08-24 09:30:52,321 DEBUG: Best view : MiRNA__
+2016-08-24 09:30:54,169 DEBUG: Start: Iteration 30
+2016-08-24 09:30:54,186 DEBUG: View 0 : 0.475308641975
+2016-08-24 09:30:54,194 DEBUG: View 1 : 0.487654320988
+2016-08-24 09:30:54,232 DEBUG: View 2 : 0.58024691358
+2016-08-24 09:30:54,239 DEBUG: View 3 : 0.376543209877
+2016-08-24 09:30:54,355 DEBUG: Best view : RANSeq_
+2016-08-24 09:30:56,248 DEBUG: Start: Iteration 31
+2016-08-24 09:30:56,266 DEBUG: View 0 : 0.586419753086
+2016-08-24 09:30:56,274 DEBUG: View 1 : 0.407407407407
+2016-08-24 09:30:56,312 DEBUG: View 2 : 0.66049382716
+2016-08-24 09:30:56,320 DEBUG: View 3 : 0.549382716049
+2016-08-24 09:30:56,442 DEBUG: Best view : RANSeq_
+2016-08-24 09:30:58,403 DEBUG: Start: Iteration 32
+2016-08-24 09:30:58,420 DEBUG: View 0 : 0.469135802469
+2016-08-24 09:30:58,428 DEBUG: View 1 : 0.734567901235
+2016-08-24 09:30:58,465 DEBUG: View 2 : 0.567901234568
+2016-08-24 09:30:58,472 DEBUG: View 3 : 0.506172839506
+2016-08-24 09:30:58,592 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:00,607 DEBUG: Start: Iteration 33
+2016-08-24 09:31:00,623 DEBUG: View 0 : 0.493827160494
+2016-08-24 09:31:00,631 DEBUG: View 1 : 0.685185185185
+2016-08-24 09:31:00,668 DEBUG: View 2 : 0.41975308642
+2016-08-24 09:31:00,676 DEBUG: View 3 : 0.487654320988
+2016-08-24 09:31:00,798 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:02,869 DEBUG: Start: Iteration 34
+2016-08-24 09:31:02,885 DEBUG: View 0 : 0.425925925926
+2016-08-24 09:31:02,893 DEBUG: View 1 : 0.567901234568
+2016-08-24 09:31:02,931 DEBUG: View 2 : 0.425925925926
+2016-08-24 09:31:02,939 DEBUG: View 3 : 0.462962962963
+2016-08-24 09:31:03,064 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:05,264 DEBUG: Start: Iteration 35
+2016-08-24 09:31:05,281 DEBUG: View 0 : 0.611111111111
+2016-08-24 09:31:05,289 DEBUG: View 1 : 0.444444444444
+2016-08-24 09:31:05,327 DEBUG: View 2 : 0.456790123457
+2016-08-24 09:31:05,334 DEBUG: View 3 : 0.567901234568
+2016-08-24 09:31:05,465 DEBUG: Best view : Methyl_
+2016-08-24 09:31:07,724 DEBUG: Start: Iteration 36
+2016-08-24 09:31:07,741 DEBUG: View 0 : 0.296296296296
+2016-08-24 09:31:07,749 DEBUG: View 1 : 0.635802469136
+2016-08-24 09:31:07,787 DEBUG: View 2 : 0.487654320988
+2016-08-24 09:31:07,795 DEBUG: View 3 : 0.506172839506
+2016-08-24 09:31:07,928 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:10,248 DEBUG: Start: Iteration 37
+2016-08-24 09:31:10,264 DEBUG: View 0 : 0.364197530864
+2016-08-24 09:31:10,272 DEBUG: View 1 : 0.623456790123
+2016-08-24 09:31:10,309 DEBUG: View 2 : 0.518518518519
+2016-08-24 09:31:10,317 DEBUG: View 3 : 0.586419753086
+2016-08-24 09:31:10,448 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:12,764 DEBUG: Start: Iteration 38
+2016-08-24 09:31:12,781 DEBUG: View 0 : 0.567901234568
+2016-08-24 09:31:12,789 DEBUG: View 1 : 0.66049382716
+2016-08-24 09:31:12,825 DEBUG: View 2 : 0.561728395062
+2016-08-24 09:31:12,833 DEBUG: View 3 : 0.41975308642
+2016-08-24 09:31:12,966 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:15,340 DEBUG: Start: Iteration 39
+2016-08-24 09:31:15,356 DEBUG: View 0 : 0.432098765432
+2016-08-24 09:31:15,364 DEBUG: View 1 : 0.654320987654
+2016-08-24 09:31:15,402 DEBUG: View 2 : 0.574074074074
+2016-08-24 09:31:15,410 DEBUG: View 3 : 0.450617283951
+2016-08-24 09:31:15,550 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:17,981 DEBUG: Start: Iteration 40
+2016-08-24 09:31:17,998 DEBUG: View 0 : 0.598765432099
+2016-08-24 09:31:18,006 DEBUG: View 1 : 0.623456790123
+2016-08-24 09:31:18,043 DEBUG: View 2 : 0.555555555556
+2016-08-24 09:31:18,051 DEBUG: View 3 : 0.530864197531
+2016-08-24 09:31:18,189 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:20,681 DEBUG: Start: Iteration 41
+2016-08-24 09:31:20,699 DEBUG: View 0 : 0.5
+2016-08-24 09:31:20,706 DEBUG: View 1 : 0.716049382716
+2016-08-24 09:31:20,744 DEBUG: View 2 : 0.388888888889
+2016-08-24 09:31:20,751 DEBUG: View 3 : 0.617283950617
+2016-08-24 09:31:20,895 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:23,510 DEBUG: Start: Iteration 42
+2016-08-24 09:31:23,528 DEBUG: View 0 : 0.388888888889
+2016-08-24 09:31:23,536 DEBUG: View 1 : 0.654320987654
+2016-08-24 09:31:23,574 DEBUG: View 2 : 0.58024691358
+2016-08-24 09:31:23,582 DEBUG: View 3 : 0.407407407407
+2016-08-24 09:31:23,729 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:26,574 DEBUG: Start: Iteration 43
+2016-08-24 09:31:26,592 DEBUG: View 0 : 0.481481481481
+2016-08-24 09:31:26,600 DEBUG: View 1 : 0.604938271605
+2016-08-24 09:31:26,638 DEBUG: View 2 : 0.481481481481
+2016-08-24 09:31:26,646 DEBUG: View 3 : 0.407407407407
+2016-08-24 09:31:26,793 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:29,678 DEBUG: Start: Iteration 44
+2016-08-24 09:31:29,697 DEBUG: View 0 : 0.462962962963
+2016-08-24 09:31:29,706 DEBUG: View 1 : 0.561728395062
+2016-08-24 09:31:29,749 DEBUG: View 2 : 0.537037037037
+2016-08-24 09:31:29,758 DEBUG: View 3 : 0.543209876543
+2016-08-24 09:31:29,929 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:32,694 DEBUG: Start: Iteration 45
+2016-08-24 09:31:32,711 DEBUG: View 0 : 0.530864197531
+2016-08-24 09:31:32,719 DEBUG: View 1 : 0.679012345679
+2016-08-24 09:31:32,756 DEBUG: View 2 : 0.358024691358
+2016-08-24 09:31:32,764 DEBUG: View 3 : 0.518518518519
+2016-08-24 09:31:32,917 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:35,983 DEBUG: Start: Iteration 46
+2016-08-24 09:31:36,000 DEBUG: View 0 : 0.475308641975
+2016-08-24 09:31:36,008 DEBUG: View 1 : 0.382716049383
+2016-08-24 09:31:36,045 DEBUG: View 2 : 0.493827160494
+2016-08-24 09:31:36,053 DEBUG: View 3 : 0.475308641975
+2016-08-24 09:31:36,053 WARNING: All bad for iteration 45
+2016-08-24 09:31:36,209 DEBUG: Best view : RANSeq_
+2016-08-24 09:31:39,103 DEBUG: Start: Iteration 47
+2016-08-24 09:31:39,122 DEBUG: View 0 : 0.611111111111
+2016-08-24 09:31:39,130 DEBUG: View 1 : 0.512345679012
+2016-08-24 09:31:39,174 DEBUG: View 2 : 0.462962962963
+2016-08-24 09:31:39,182 DEBUG: View 3 : 0.506172839506
+2016-08-24 09:31:39,352 DEBUG: Best view : Methyl_
+2016-08-24 09:31:42,556 DEBUG: Start: Iteration 48
+2016-08-24 09:31:42,572 DEBUG: View 0 : 0.530864197531
+2016-08-24 09:31:42,580 DEBUG: View 1 : 0.604938271605
+2016-08-24 09:31:42,619 DEBUG: View 2 : 0.518518518519
+2016-08-24 09:31:42,628 DEBUG: View 3 : 0.407407407407
+2016-08-24 09:31:42,789 DEBUG: Best view : MiRNA__
+2016-08-24 09:31:46,061 DEBUG: Start: Iteration 49
+2016-08-24 09:31:46,078 DEBUG: View 0 : 0.413580246914
+2016-08-24 09:31:46,086 DEBUG: View 1 : 0.549382716049
+2016-08-24 09:31:46,124 DEBUG: View 2 : 0.62962962963
+2016-08-24 09:31:46,131 DEBUG: View 3 : 0.407407407407
+2016-08-24 09:31:46,294 DEBUG: Best view : RANSeq_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093148-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093148-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..81280fafd9f5ba7f5f428ea342b0a231f53b3de1
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093148-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,30 @@
+2016-08-24 09:31:48,286 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:31:48,286 INFO: Info: Labels used: No, Yes
+2016-08-24 09:31:48,287 INFO: Info: Length of dataset:347
+2016-08-24 09:31:48,288 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:31:48,288 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:31:48,289 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:31:48,289 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:31:48,289 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:31:48,290 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:31:48,290 INFO: Done: Read Database Files
+2016-08-24 09:31:48,290 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:31:48,293 INFO: Done: Determine validation split
+2016-08-24 09:31:48,293 INFO: Start: Determine 2 folds
+2016-08-24 09:31:48,304 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:31:48,304 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:31:48,304 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:31:48,304 INFO: Done: Determine folds
+2016-08-24 09:31:48,304 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:31:48,304 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:31:48,305 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:31:55,692 DEBUG: 0.579596541787Poulet
+2016-08-24 09:31:55,692 DEBUG: 0.592103746398Poulet
+2016-08-24 09:31:55,693 DEBUG: 0.599135446686Poulet
+2016-08-24 09:31:55,694 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:31:55,694 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:31:57,621 DEBUG: 0.502997118156Poulet
+2016-08-24 09:31:57,621 DEBUG: 0.571354466859Poulet
+2016-08-24 09:31:57,621 DEBUG: 0.575331412104Poulet
+2016-08-24 09:31:57,621 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:31:57,622 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093234-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093234-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..d2aff05edd9ca76570b2d7dc018eb6430a8c89a4
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093234-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,27 @@
+2016-08-24 09:32:34,093 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:32:34,093 INFO: Info: Labels used: No, Yes
+2016-08-24 09:32:34,094 INFO: Info: Length of dataset:347
+2016-08-24 09:32:34,095 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:32:34,095 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:32:34,096 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:32:34,096 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:32:34,096 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:32:34,097 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:32:34,097 INFO: Done: Read Database Files
+2016-08-24 09:32:34,097 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:32:34,100 INFO: Done: Determine validation split
+2016-08-24 09:32:34,100 INFO: Start: Determine 2 folds
+2016-08-24 09:32:34,111 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:32:34,111 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:32:34,111 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:32:34,111 INFO: Done: Determine folds
+2016-08-24 09:32:34,111 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:32:34,112 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:32:34,112 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:32:41,471 DEBUG: 0.585014409222Poulet
+2016-08-24 09:32:41,471 DEBUG: 0.596714697406Poulet
+2016-08-24 09:32:41,472 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:32:41,472 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:32:43,398 DEBUG: 0.58386167147Poulet
+2016-08-24 09:32:43,399 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:32:43,399 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093312-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093312-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..3862f8c6dde772c5f7804dd85526bebd79f7d53e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093312-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,53 @@
+2016-08-24 09:33:12,122 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:33:12,123 INFO: Info: Labels used: No, Yes
+2016-08-24 09:33:12,123 INFO: Info: Length of dataset:347
+2016-08-24 09:33:12,124 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:33:12,124 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:33:12,125 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:33:12,125 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:33:12,125 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:33:12,126 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:33:12,126 INFO: Done: Read Database Files
+2016-08-24 09:33:12,126 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:33:12,129 INFO: Done: Determine validation split
+2016-08-24 09:33:12,129 INFO: Start: Determine 2 folds
+2016-08-24 09:33:12,143 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:33:12,143 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:33:12,143 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:33:12,143 INFO: Done: Determine folds
+2016-08-24 09:33:12,143 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:33:12,143 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:33:12,143 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:33:19,481 DEBUG: 0.596714697406Poulet
+2016-08-24 09:33:19,481 DEBUG: 0.583227665706Poulet
+2016-08-24 09:33:19,481 DEBUG: 0.591527377522Poulet
+2016-08-24 09:33:19,481 DEBUG: 0.58288184438Poulet
+2016-08-24 09:33:19,481 DEBUG: 0.535273775216Poulet
+2016-08-24 09:33:19,481 DEBUG: 0.515619596542Poulet
+2016-08-24 09:33:19,481 DEBUG: 0.523804034582Poulet
+2016-08-24 09:33:19,481 DEBUG: 0.521556195965Poulet
+2016-08-24 09:33:19,482 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:33:19,482 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:33:21,403 DEBUG: 0.58553314121Poulet
+2016-08-24 09:33:21,403 DEBUG: 0.554178674352Poulet
+2016-08-24 09:33:21,403 DEBUG: 0.53734870317Poulet
+2016-08-24 09:33:21,403 DEBUG: 0.575792507205Poulet
+2016-08-24 09:33:21,403 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:33:21,404 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:33:38,038 DEBUG: 0.576253602305Poulet
+2016-08-24 09:33:38,038 DEBUG: 0.566109510086Poulet
+2016-08-24 09:33:38,038 DEBUG: 0.577925072046Poulet
+2016-08-24 09:33:38,039 DEBUG: 0.58144092219Poulet
+2016-08-24 09:33:38,039 DEBUG: 0.502305475504Poulet
+2016-08-24 09:33:38,039 DEBUG: 0.501613832853Poulet
+2016-08-24 09:33:38,039 DEBUG: 0.50818443804Poulet
+2016-08-24 09:33:38,039 DEBUG: 0.52795389049Poulet
+2016-08-24 09:33:38,039 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:33:38,040 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:33:39,777 DEBUG: 0.551296829971Poulet
+2016-08-24 09:33:39,777 DEBUG: 0.591008645533Poulet
+2016-08-24 09:33:39,777 DEBUG: 0.582478386167Poulet
+2016-08-24 09:33:39,777 DEBUG: 0.567838616715Poulet
+2016-08-24 09:33:39,777 DEBUG: 0.517002881844Poulet
+2016-08-24 09:33:39,777 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:33:39,778 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093355-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093355-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..2c779d8c58a02ca2bdc27dcb7a71399efd035c26
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093355-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,14742 @@
+2016-08-24 09:33:55,099 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:33:55,100 INFO: Info: Labels used: No, Yes
+2016-08-24 09:33:55,100 INFO: Info: Length of dataset:347
+2016-08-24 09:33:55,101 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:33:55,101 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:33:55,102 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:33:55,102 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:33:55,103 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:33:55,103 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:33:55,103 INFO: Done: Read Database Files
+2016-08-24 09:33:55,103 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:33:55,107 INFO: Done: Determine validation split
+2016-08-24 09:33:55,107 INFO: Start: Determine 2 folds
+2016-08-24 09:33:55,116 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:33:55,116 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:33:55,116 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:33:55,116 INFO: Done: Determine folds
+2016-08-24 09:33:55,117 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:33:55,117 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:33:55,117 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:34:02,435 DEBUG: 0.591988472622Poulet
+2016-08-24 09:34:02,435 DEBUG: 0.58386167147Poulet
+2016-08-24 09:34:02,435 DEBUG: 0.517752161383Poulet
+2016-08-24 09:34:02,435 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:34:02,436 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:34:04,356 DEBUG: 0.533083573487Poulet
+2016-08-24 09:34:04,356 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:34:04,357 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:34:20,901 DEBUG: 0.582997118156Poulet
+2016-08-24 09:34:20,902 DEBUG: 0.549682997118Poulet
+2016-08-24 09:34:20,902 DEBUG: 0.503746397695Poulet
+2016-08-24 09:34:20,902 DEBUG: 0.50674351585Poulet
+2016-08-24 09:34:20,902 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:34:20,903 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:34:22,667 DEBUG: 0.567319884726Poulet
+2016-08-24 09:34:22,667 DEBUG: 0.554409221902Poulet
+2016-08-24 09:34:22,667 DEBUG: 0.504553314121Poulet
+2016-08-24 09:34:22,667 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:34:22,668 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:34:59,961 DEBUG: 0.553544668588Poulet
+2016-08-24 09:34:59,961 DEBUG: 0.549452449568Poulet
+2016-08-24 09:34:59,961 DEBUG: 0.53325648415Poulet
+2016-08-24 09:34:59,962 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:34:59,962 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:34:59,962 INFO: Start: Fold number 1
+2016-08-24 09:35:01,610 DEBUG: Start: Iteration 1
+2016-08-24 09:35:01,630 DEBUG: View 0 : 0.615384615385
+2016-08-24 09:35:01,638 DEBUG: View 1 : 0.615384615385
+2016-08-24 09:35:01,679 DEBUG: View 2 : 0.615384615385
+2016-08-24 09:35:01,687 DEBUG: View 3 : 0.615384615385
+2016-08-24 09:35:01,730 DEBUG: Best view : Methyl_
+2016-08-24 09:35:01,811 DEBUG: Start: Iteration 2
+2016-08-24 09:35:01,829 DEBUG: View 0 : 0.666666666667
+2016-08-24 09:35:01,838 DEBUG: View 1 : 0.564102564103
+2016-08-24 09:35:01,876 DEBUG: View 2 : 0.564102564103
+2016-08-24 09:35:01,884 DEBUG: View 3 : 0.5
+2016-08-24 09:35:01,931 DEBUG: Best view : Methyl_
+2016-08-24 09:35:02,070 DEBUG: Start: Iteration 3
+2016-08-24 09:35:02,086 DEBUG: View 0 : 0.461538461538
+2016-08-24 09:35:02,094 DEBUG: View 1 : 0.538461538462
+2016-08-24 09:35:02,130 DEBUG: View 2 : 0.512820512821
+2016-08-24 09:35:02,138 DEBUG: View 3 : 0.5
+2016-08-24 09:35:02,191 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:02,387 DEBUG: Start: Iteration 4
+2016-08-24 09:35:02,404 DEBUG: View 0 : 0.538461538462
+2016-08-24 09:35:02,412 DEBUG: View 1 : 0.525641025641
+2016-08-24 09:35:02,448 DEBUG: View 2 : 0.455128205128
+2016-08-24 09:35:02,456 DEBUG: View 3 : 0.512820512821
+2016-08-24 09:35:02,512 DEBUG: Best view : Methyl_
+2016-08-24 09:35:02,768 DEBUG: Start: Iteration 5
+2016-08-24 09:35:02,784 DEBUG: View 0 : 0.448717948718
+2016-08-24 09:35:02,792 DEBUG: View 1 : 0.647435897436
+2016-08-24 09:35:02,828 DEBUG: View 2 : 0.455128205128
+2016-08-24 09:35:02,836 DEBUG: View 3 : 0.461538461538
+2016-08-24 09:35:02,895 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:03,209 DEBUG: Start: Iteration 6
+2016-08-24 09:35:03,225 DEBUG: View 0 : 0.628205128205
+2016-08-24 09:35:03,233 DEBUG: View 1 : 0.679487179487
+2016-08-24 09:35:03,269 DEBUG: View 2 : 0.391025641026
+2016-08-24 09:35:03,277 DEBUG: View 3 : 0.544871794872
+2016-08-24 09:35:03,339 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:03,710 DEBUG: Start: Iteration 7
+2016-08-24 09:35:03,727 DEBUG: View 0 : 0.538461538462
+2016-08-24 09:35:03,734 DEBUG: View 1 : 0.512820512821
+2016-08-24 09:35:03,771 DEBUG: View 2 : 0.391025641026
+2016-08-24 09:35:03,778 DEBUG: View 3 : 0.5
+2016-08-24 09:35:03,842 DEBUG: Best view : Methyl_
+2016-08-24 09:35:04,273 DEBUG: Start: Iteration 8
+2016-08-24 09:35:04,290 DEBUG: View 0 : 0.442307692308
+2016-08-24 09:35:04,297 DEBUG: View 1 : 0.608974358974
+2016-08-24 09:35:04,334 DEBUG: View 2 : 0.474358974359
+2016-08-24 09:35:04,341 DEBUG: View 3 : 0.50641025641
+2016-08-24 09:35:04,407 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:04,895 DEBUG: Start: Iteration 9
+2016-08-24 09:35:04,911 DEBUG: View 0 : 0.435897435897
+2016-08-24 09:35:04,919 DEBUG: View 1 : 0.525641025641
+2016-08-24 09:35:04,957 DEBUG: View 2 : 0.602564102564
+2016-08-24 09:35:04,964 DEBUG: View 3 : 0.608974358974
+2016-08-24 09:35:05,033 DEBUG: Best view : Clinic_
+2016-08-24 09:35:05,579 DEBUG: Start: Iteration 10
+2016-08-24 09:35:05,595 DEBUG: View 0 : 0.596153846154
+2016-08-24 09:35:05,603 DEBUG: View 1 : 0.371794871795
+2016-08-24 09:35:05,639 DEBUG: View 2 : 0.532051282051
+2016-08-24 09:35:05,646 DEBUG: View 3 : 0.442307692308
+2016-08-24 09:35:05,717 DEBUG: Best view : Methyl_
+2016-08-24 09:35:06,322 DEBUG: Start: Iteration 11
+2016-08-24 09:35:06,338 DEBUG: View 0 : 0.474358974359
+2016-08-24 09:35:06,346 DEBUG: View 1 : 0.608974358974
+2016-08-24 09:35:06,382 DEBUG: View 2 : 0.608974358974
+2016-08-24 09:35:06,389 DEBUG: View 3 : 0.557692307692
+2016-08-24 09:35:06,462 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:07,123 DEBUG: Start: Iteration 12
+2016-08-24 09:35:07,140 DEBUG: View 0 : 0.5
+2016-08-24 09:35:07,147 DEBUG: View 1 : 0.391025641026
+2016-08-24 09:35:07,184 DEBUG: View 2 : 0.551282051282
+2016-08-24 09:35:07,192 DEBUG: View 3 : 0.50641025641
+2016-08-24 09:35:07,266 DEBUG: Best view : RANSeq_
+2016-08-24 09:35:08,000 DEBUG: Start: Iteration 13
+2016-08-24 09:35:08,016 DEBUG: View 0 : 0.519230769231
+2016-08-24 09:35:08,024 DEBUG: View 1 : 0.647435897436
+2016-08-24 09:35:08,060 DEBUG: View 2 : 0.557692307692
+2016-08-24 09:35:08,068 DEBUG: View 3 : 0.634615384615
+2016-08-24 09:35:08,144 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:08,935 DEBUG: Start: Iteration 14
+2016-08-24 09:35:08,951 DEBUG: View 0 : 0.461538461538
+2016-08-24 09:35:08,959 DEBUG: View 1 : 0.519230769231
+2016-08-24 09:35:08,995 DEBUG: View 2 : 0.474358974359
+2016-08-24 09:35:09,003 DEBUG: View 3 : 0.435897435897
+2016-08-24 09:35:09,080 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:09,927 DEBUG: Start: Iteration 15
+2016-08-24 09:35:09,943 DEBUG: View 0 : 0.442307692308
+2016-08-24 09:35:09,951 DEBUG: View 1 : 0.474358974359
+2016-08-24 09:35:09,987 DEBUG: View 2 : 0.589743589744
+2016-08-24 09:35:09,995 DEBUG: View 3 : 0.410256410256
+2016-08-24 09:35:10,074 DEBUG: Best view : RANSeq_
+2016-08-24 09:35:10,994 DEBUG: Start: Iteration 16
+2016-08-24 09:35:11,011 DEBUG: View 0 : 0.455128205128
+2016-08-24 09:35:11,019 DEBUG: View 1 : 0.628205128205
+2016-08-24 09:35:11,056 DEBUG: View 2 : 0.532051282051
+2016-08-24 09:35:11,064 DEBUG: View 3 : 0.50641025641
+2016-08-24 09:35:11,146 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:12,120 DEBUG: Start: Iteration 17
+2016-08-24 09:35:12,136 DEBUG: View 0 : 0.621794871795
+2016-08-24 09:35:12,144 DEBUG: View 1 : 0.551282051282
+2016-08-24 09:35:12,181 DEBUG: View 2 : 0.49358974359
+2016-08-24 09:35:12,188 DEBUG: View 3 : 0.455128205128
+2016-08-24 09:35:12,273 DEBUG: Best view : Methyl_
+2016-08-24 09:35:13,308 DEBUG: Start: Iteration 18
+2016-08-24 09:35:13,325 DEBUG: View 0 : 0.557692307692
+2016-08-24 09:35:13,332 DEBUG: View 1 : 0.608974358974
+2016-08-24 09:35:13,369 DEBUG: View 2 : 0.49358974359
+2016-08-24 09:35:13,376 DEBUG: View 3 : 0.512820512821
+2016-08-24 09:35:13,464 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:14,557 DEBUG: Start: Iteration 19
+2016-08-24 09:35:14,573 DEBUG: View 0 : 0.416666666667
+2016-08-24 09:35:14,581 DEBUG: View 1 : 0.403846153846
+2016-08-24 09:35:14,618 DEBUG: View 2 : 0.589743589744
+2016-08-24 09:35:14,626 DEBUG: View 3 : 0.403846153846
+2016-08-24 09:35:14,714 DEBUG: Best view : RANSeq_
+2016-08-24 09:35:15,878 DEBUG: Start: Iteration 20
+2016-08-24 09:35:15,895 DEBUG: View 0 : 0.467948717949
+2016-08-24 09:35:15,902 DEBUG: View 1 : 0.685897435897
+2016-08-24 09:35:15,939 DEBUG: View 2 : 0.628205128205
+2016-08-24 09:35:15,946 DEBUG: View 3 : 0.49358974359
+2016-08-24 09:35:16,038 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:17,259 DEBUG: Start: Iteration 21
+2016-08-24 09:35:17,275 DEBUG: View 0 : 0.564102564103
+2016-08-24 09:35:17,283 DEBUG: View 1 : 0.711538461538
+2016-08-24 09:35:17,319 DEBUG: View 2 : 0.429487179487
+2016-08-24 09:35:17,327 DEBUG: View 3 : 0.532051282051
+2016-08-24 09:35:17,419 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:18,697 DEBUG: Start: Iteration 22
+2016-08-24 09:35:18,713 DEBUG: View 0 : 0.538461538462
+2016-08-24 09:35:18,721 DEBUG: View 1 : 0.634615384615
+2016-08-24 09:35:18,757 DEBUG: View 2 : 0.525641025641
+2016-08-24 09:35:18,765 DEBUG: View 3 : 0.570512820513
+2016-08-24 09:35:18,860 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:20,195 DEBUG: Start: Iteration 23
+2016-08-24 09:35:20,212 DEBUG: View 0 : 0.525641025641
+2016-08-24 09:35:20,219 DEBUG: View 1 : 0.641025641026
+2016-08-24 09:35:20,256 DEBUG: View 2 : 0.551282051282
+2016-08-24 09:35:20,264 DEBUG: View 3 : 0.602564102564
+2016-08-24 09:35:20,360 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:21,760 DEBUG: Start: Iteration 24
+2016-08-24 09:35:21,776 DEBUG: View 0 : 0.762820512821
+2016-08-24 09:35:21,784 DEBUG: View 1 : 0.628205128205
+2016-08-24 09:35:21,820 DEBUG: View 2 : 0.371794871795
+2016-08-24 09:35:21,828 DEBUG: View 3 : 0.461538461538
+2016-08-24 09:35:21,926 DEBUG: Best view : Methyl_
+2016-08-24 09:35:23,376 DEBUG: Start: Iteration 25
+2016-08-24 09:35:23,392 DEBUG: View 0 : 0.487179487179
+2016-08-24 09:35:23,400 DEBUG: View 1 : 0.391025641026
+2016-08-24 09:35:23,436 DEBUG: View 2 : 0.487179487179
+2016-08-24 09:35:23,444 DEBUG: View 3 : 0.403846153846
+2016-08-24 09:35:23,444 WARNING: All bad for iteration 24
+2016-08-24 09:35:23,545 DEBUG: Best view : Methyl_
+2016-08-24 09:35:25,059 DEBUG: Start: Iteration 26
+2016-08-24 09:35:25,076 DEBUG: View 0 : 0.602564102564
+2016-08-24 09:35:25,084 DEBUG: View 1 : 0.608974358974
+2016-08-24 09:35:25,121 DEBUG: View 2 : 0.5
+2016-08-24 09:35:25,129 DEBUG: View 3 : 0.467948717949
+2016-08-24 09:35:25,232 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:26,805 DEBUG: Start: Iteration 27
+2016-08-24 09:35:26,821 DEBUG: View 0 : 0.544871794872
+2016-08-24 09:35:26,829 DEBUG: View 1 : 0.416666666667
+2016-08-24 09:35:26,866 DEBUG: View 2 : 0.557692307692
+2016-08-24 09:35:26,873 DEBUG: View 3 : 0.570512820513
+2016-08-24 09:35:26,978 DEBUG: Best view : Clinic_
+2016-08-24 09:35:28,607 DEBUG: Start: Iteration 28
+2016-08-24 09:35:28,624 DEBUG: View 0 : 0.608974358974
+2016-08-24 09:35:28,632 DEBUG: View 1 : 0.519230769231
+2016-08-24 09:35:28,668 DEBUG: View 2 : 0.467948717949
+2016-08-24 09:35:28,676 DEBUG: View 3 : 0.50641025641
+2016-08-24 09:35:28,783 DEBUG: Best view : Methyl_
+2016-08-24 09:35:30,474 DEBUG: Start: Iteration 29
+2016-08-24 09:35:30,490 DEBUG: View 0 : 0.602564102564
+2016-08-24 09:35:30,498 DEBUG: View 1 : 0.480769230769
+2016-08-24 09:35:30,534 DEBUG: View 2 : 0.474358974359
+2016-08-24 09:35:30,541 DEBUG: View 3 : 0.589743589744
+2016-08-24 09:35:30,651 DEBUG: Best view : Methyl_
+2016-08-24 09:35:32,412 DEBUG: Start: Iteration 30
+2016-08-24 09:35:32,428 DEBUG: View 0 : 0.455128205128
+2016-08-24 09:35:32,436 DEBUG: View 1 : 0.429487179487
+2016-08-24 09:35:32,472 DEBUG: View 2 : 0.423076923077
+2016-08-24 09:35:32,479 DEBUG: View 3 : 0.647435897436
+2016-08-24 09:35:32,591 DEBUG: Best view : Clinic_
+2016-08-24 09:35:34,461 DEBUG: Start: Iteration 31
+2016-08-24 09:35:34,480 DEBUG: View 0 : 0.576923076923
+2016-08-24 09:35:34,488 DEBUG: View 1 : 0.615384615385
+2016-08-24 09:35:34,526 DEBUG: View 2 : 0.448717948718
+2016-08-24 09:35:34,533 DEBUG: View 3 : 0.442307692308
+2016-08-24 09:35:34,653 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:36,567 DEBUG: Start: Iteration 32
+2016-08-24 09:35:36,583 DEBUG: View 0 : 0.602564102564
+2016-08-24 09:35:36,591 DEBUG: View 1 : 0.647435897436
+2016-08-24 09:35:36,628 DEBUG: View 2 : 0.519230769231
+2016-08-24 09:35:36,635 DEBUG: View 3 : 0.602564102564
+2016-08-24 09:35:36,760 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:38,858 DEBUG: Start: Iteration 33
+2016-08-24 09:35:38,875 DEBUG: View 0 : 0.50641025641
+2016-08-24 09:35:38,883 DEBUG: View 1 : 0.371794871795
+2016-08-24 09:35:38,920 DEBUG: View 2 : 0.403846153846
+2016-08-24 09:35:38,928 DEBUG: View 3 : 0.641025641026
+2016-08-24 09:35:39,047 DEBUG: Best view : Clinic_
+2016-08-24 09:35:41,049 DEBUG: Start: Iteration 34
+2016-08-24 09:35:41,066 DEBUG: View 0 : 0.596153846154
+2016-08-24 09:35:41,074 DEBUG: View 1 : 0.641025641026
+2016-08-24 09:35:41,110 DEBUG: View 2 : 0.448717948718
+2016-08-24 09:35:41,118 DEBUG: View 3 : 0.397435897436
+2016-08-24 09:35:41,241 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:43,293 DEBUG: Start: Iteration 35
+2016-08-24 09:35:43,310 DEBUG: View 0 : 0.5
+2016-08-24 09:35:43,317 DEBUG: View 1 : 0.666666666667
+2016-08-24 09:35:43,354 DEBUG: View 2 : 0.557692307692
+2016-08-24 09:35:43,361 DEBUG: View 3 : 0.576923076923
+2016-08-24 09:35:43,483 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:45,576 DEBUG: Start: Iteration 36
+2016-08-24 09:35:45,593 DEBUG: View 0 : 0.435897435897
+2016-08-24 09:35:45,600 DEBUG: View 1 : 0.358974358974
+2016-08-24 09:35:45,636 DEBUG: View 2 : 0.487179487179
+2016-08-24 09:35:45,644 DEBUG: View 3 : 0.570512820513
+2016-08-24 09:35:45,768 DEBUG: Best view : Clinic_
+2016-08-24 09:35:47,921 DEBUG: Start: Iteration 37
+2016-08-24 09:35:47,937 DEBUG: View 0 : 0.583333333333
+2016-08-24 09:35:47,945 DEBUG: View 1 : 0.647435897436
+2016-08-24 09:35:47,981 DEBUG: View 2 : 0.583333333333
+2016-08-24 09:35:47,989 DEBUG: View 3 : 0.557692307692
+2016-08-24 09:35:48,116 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:50,347 DEBUG: Start: Iteration 38
+2016-08-24 09:35:50,364 DEBUG: View 0 : 0.423076923077
+2016-08-24 09:35:50,372 DEBUG: View 1 : 0.685897435897
+2016-08-24 09:35:50,409 DEBUG: View 2 : 0.50641025641
+2016-08-24 09:35:50,416 DEBUG: View 3 : 0.410256410256
+2016-08-24 09:35:50,547 DEBUG: Best view : MiRNA__
+2016-08-24 09:35:52,847 DEBUG: Start: Iteration 39
+2016-08-24 09:35:52,863 DEBUG: View 0 : 0.423076923077
+2016-08-24 09:35:52,871 DEBUG: View 1 : 0.532051282051
+2016-08-24 09:35:52,909 DEBUG: View 2 : 0.596153846154
+2016-08-24 09:35:52,917 DEBUG: View 3 : 0.621794871795
+2016-08-24 09:35:53,050 DEBUG: Best view : Clinic_
+2016-08-24 09:35:55,388 DEBUG: Start: Iteration 40
+2016-08-24 09:35:55,405 DEBUG: View 0 : 0.628205128205
+2016-08-24 09:35:55,413 DEBUG: View 1 : 0.474358974359
+2016-08-24 09:35:55,450 DEBUG: View 2 : 0.474358974359
+2016-08-24 09:35:55,459 DEBUG: View 3 : 0.448717948718
+2016-08-24 09:35:55,654 DEBUG: Best view : Methyl_
+2016-08-24 09:35:58,192 DEBUG: Start: Iteration 41
+2016-08-24 09:35:58,210 DEBUG: View 0 : 0.615384615385
+2016-08-24 09:35:58,219 DEBUG: View 1 : 0.628205128205
+2016-08-24 09:35:58,261 DEBUG: View 2 : 0.570512820513
+2016-08-24 09:35:58,270 DEBUG: View 3 : 0.435897435897
+2016-08-24 09:35:58,469 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:01,082 DEBUG: Start: Iteration 42
+2016-08-24 09:36:01,099 DEBUG: View 0 : 0.705128205128
+2016-08-24 09:36:01,107 DEBUG: View 1 : 0.647435897436
+2016-08-24 09:36:01,144 DEBUG: View 2 : 0.435897435897
+2016-08-24 09:36:01,152 DEBUG: View 3 : 0.602564102564
+2016-08-24 09:36:01,298 DEBUG: Best view : Methyl_
+2016-08-24 09:36:04,147 DEBUG: Start: Iteration 43
+2016-08-24 09:36:04,173 DEBUG: View 0 : 0.448717948718
+2016-08-24 09:36:04,182 DEBUG: View 1 : 0.416666666667
+2016-08-24 09:36:04,224 DEBUG: View 2 : 0.480769230769
+2016-08-24 09:36:04,236 DEBUG: View 3 : 0.551282051282
+2016-08-24 09:36:04,378 DEBUG: Best view : Clinic_
+2016-08-24 09:36:07,254 DEBUG: Start: Iteration 44
+2016-08-24 09:36:07,271 DEBUG: View 0 : 0.564102564103
+2016-08-24 09:36:07,278 DEBUG: View 1 : 0.660256410256
+2016-08-24 09:36:07,315 DEBUG: View 2 : 0.557692307692
+2016-08-24 09:36:07,322 DEBUG: View 3 : 0.557692307692
+2016-08-24 09:36:07,468 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:10,373 DEBUG: Start: Iteration 45
+2016-08-24 09:36:10,391 DEBUG: View 0 : 0.371794871795
+2016-08-24 09:36:10,400 DEBUG: View 1 : 0.673076923077
+2016-08-24 09:36:10,447 DEBUG: View 2 : 0.538461538462
+2016-08-24 09:36:10,456 DEBUG: View 3 : 0.487179487179
+2016-08-24 09:36:10,702 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:13,728 DEBUG: Start: Iteration 46
+2016-08-24 09:36:13,744 DEBUG: View 0 : 0.532051282051
+2016-08-24 09:36:13,752 DEBUG: View 1 : 0.576923076923
+2016-08-24 09:36:13,789 DEBUG: View 2 : 0.487179487179
+2016-08-24 09:36:13,797 DEBUG: View 3 : 0.628205128205
+2016-08-24 09:36:13,944 DEBUG: Best view : Clinic_
+2016-08-24 09:36:16,698 DEBUG: Start: Iteration 47
+2016-08-24 09:36:16,714 DEBUG: View 0 : 0.410256410256
+2016-08-24 09:36:16,722 DEBUG: View 1 : 0.532051282051
+2016-08-24 09:36:16,759 DEBUG: View 2 : 0.487179487179
+2016-08-24 09:36:16,767 DEBUG: View 3 : 0.448717948718
+2016-08-24 09:36:16,916 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:19,727 DEBUG: Start: Iteration 48
+2016-08-24 09:36:19,743 DEBUG: View 0 : 0.423076923077
+2016-08-24 09:36:19,751 DEBUG: View 1 : 0.615384615385
+2016-08-24 09:36:19,787 DEBUG: View 2 : 0.532051282051
+2016-08-24 09:36:19,794 DEBUG: View 3 : 0.583333333333
+2016-08-24 09:36:19,945 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:22,795 DEBUG: Start: Iteration 49
+2016-08-24 09:36:22,811 DEBUG: View 0 : 0.487179487179
+2016-08-24 09:36:22,819 DEBUG: View 1 : 0.608974358974
+2016-08-24 09:36:22,855 DEBUG: View 2 : 0.378205128205
+2016-08-24 09:36:22,863 DEBUG: View 3 : 0.596153846154
+2016-08-24 09:36:23,015 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:25,918 DEBUG: Start: Iteration 50
+2016-08-24 09:36:25,934 DEBUG: View 0 : 0.423076923077
+2016-08-24 09:36:25,942 DEBUG: View 1 : 0.365384615385
+2016-08-24 09:36:25,979 DEBUG: View 2 : 0.570512820513
+2016-08-24 09:36:25,987 DEBUG: View 3 : 0.544871794872
+2016-08-24 09:36:26,144 DEBUG: Best view : RANSeq_
+2016-08-24 09:36:29,125 DEBUG: Start: Iteration 51
+2016-08-24 09:36:29,141 DEBUG: View 0 : 0.602564102564
+2016-08-24 09:36:29,149 DEBUG: View 1 : 0.653846153846
+2016-08-24 09:36:29,185 DEBUG: View 2 : 0.397435897436
+2016-08-24 09:36:29,193 DEBUG: View 3 : 0.615384615385
+2016-08-24 09:36:29,350 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:32,554 DEBUG: Start: Iteration 52
+2016-08-24 09:36:32,572 DEBUG: View 0 : 0.621794871795
+2016-08-24 09:36:32,580 DEBUG: View 1 : 0.692307692308
+2016-08-24 09:36:32,617 DEBUG: View 2 : 0.435897435897
+2016-08-24 09:36:32,625 DEBUG: View 3 : 0.608974358974
+2016-08-24 09:36:32,784 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:35,871 INFO: Start: Classification
+2016-08-24 09:36:43,411 INFO: Done: Fold number 1
+2016-08-24 09:36:43,411 INFO: Start: Fold number 2
+2016-08-24 09:36:44,984 DEBUG: Start: Iteration 1
+2016-08-24 09:36:44,998 DEBUG: View 0 : 0.382165605096
+2016-08-24 09:36:45,006 DEBUG: View 1 : 0.617834394904
+2016-08-24 09:36:45,042 DEBUG: View 2 : 0.369426751592
+2016-08-24 09:36:45,049 DEBUG: View 3 : 0.617834394904
+2016-08-24 09:36:45,089 DEBUG: Best view : Methyl_
+2016-08-24 09:36:45,164 DEBUG: Start: Iteration 2
+2016-08-24 09:36:45,180 DEBUG: View 0 : 0.43949044586
+2016-08-24 09:36:45,188 DEBUG: View 1 : 0.649681528662
+2016-08-24 09:36:45,224 DEBUG: View 2 : 0.541401273885
+2016-08-24 09:36:45,231 DEBUG: View 3 : 0.509554140127
+2016-08-24 09:36:45,276 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:45,408 DEBUG: Start: Iteration 3
+2016-08-24 09:36:45,424 DEBUG: View 0 : 0.420382165605
+2016-08-24 09:36:45,432 DEBUG: View 1 : 0.630573248408
+2016-08-24 09:36:45,467 DEBUG: View 2 : 0.535031847134
+2016-08-24 09:36:45,475 DEBUG: View 3 : 0.388535031847
+2016-08-24 09:36:45,527 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:45,717 DEBUG: Start: Iteration 4
+2016-08-24 09:36:45,733 DEBUG: View 0 : 0.375796178344
+2016-08-24 09:36:45,741 DEBUG: View 1 : 0.573248407643
+2016-08-24 09:36:45,777 DEBUG: View 2 : 0.490445859873
+2016-08-24 09:36:45,784 DEBUG: View 3 : 0.503184713376
+2016-08-24 09:36:45,839 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:46,086 DEBUG: Start: Iteration 5
+2016-08-24 09:36:46,103 DEBUG: View 0 : 0.566878980892
+2016-08-24 09:36:46,110 DEBUG: View 1 : 0.585987261146
+2016-08-24 09:36:46,146 DEBUG: View 2 : 0.566878980892
+2016-08-24 09:36:46,154 DEBUG: View 3 : 0.579617834395
+2016-08-24 09:36:46,210 DEBUG: Best view : Clinic_
+2016-08-24 09:36:46,514 DEBUG: Start: Iteration 6
+2016-08-24 09:36:46,530 DEBUG: View 0 : 0.484076433121
+2016-08-24 09:36:46,538 DEBUG: View 1 : 0.496815286624
+2016-08-24 09:36:46,574 DEBUG: View 2 : 0.56050955414
+2016-08-24 09:36:46,581 DEBUG: View 3 : 0.445859872611
+2016-08-24 09:36:46,640 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:47,001 DEBUG: Start: Iteration 7
+2016-08-24 09:36:47,018 DEBUG: View 0 : 0.541401273885
+2016-08-24 09:36:47,025 DEBUG: View 1 : 0.624203821656
+2016-08-24 09:36:47,061 DEBUG: View 2 : 0.43949044586
+2016-08-24 09:36:47,069 DEBUG: View 3 : 0.375796178344
+2016-08-24 09:36:47,129 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:47,548 DEBUG: Start: Iteration 8
+2016-08-24 09:36:47,565 DEBUG: View 0 : 0.643312101911
+2016-08-24 09:36:47,572 DEBUG: View 1 : 0.312101910828
+2016-08-24 09:36:47,608 DEBUG: View 2 : 0.420382165605
+2016-08-24 09:36:47,615 DEBUG: View 3 : 0.541401273885
+2016-08-24 09:36:47,678 DEBUG: Best view : Methyl_
+2016-08-24 09:36:48,158 DEBUG: Start: Iteration 9
+2016-08-24 09:36:48,174 DEBUG: View 0 : 0.458598726115
+2016-08-24 09:36:48,182 DEBUG: View 1 : 0.407643312102
+2016-08-24 09:36:48,217 DEBUG: View 2 : 0.445859872611
+2016-08-24 09:36:48,224 DEBUG: View 3 : 0.458598726115
+2016-08-24 09:36:48,225 WARNING: All bad for iteration 8
+2016-08-24 09:36:48,290 DEBUG: Best view : Clinic_
+2016-08-24 09:36:48,826 DEBUG: Start: Iteration 10
+2016-08-24 09:36:48,843 DEBUG: View 0 : 0.547770700637
+2016-08-24 09:36:48,851 DEBUG: View 1 : 0.566878980892
+2016-08-24 09:36:48,887 DEBUG: View 2 : 0.407643312102
+2016-08-24 09:36:48,894 DEBUG: View 3 : 0.43949044586
+2016-08-24 09:36:48,962 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:49,554 DEBUG: Start: Iteration 11
+2016-08-24 09:36:49,571 DEBUG: View 0 : 0.535031847134
+2016-08-24 09:36:49,579 DEBUG: View 1 : 0.433121019108
+2016-08-24 09:36:49,614 DEBUG: View 2 : 0.484076433121
+2016-08-24 09:36:49,622 DEBUG: View 3 : 0.420382165605
+2016-08-24 09:36:49,691 DEBUG: Best view : RANSeq_
+2016-08-24 09:36:50,358 DEBUG: Start: Iteration 12
+2016-08-24 09:36:50,374 DEBUG: View 0 : 0.770700636943
+2016-08-24 09:36:50,382 DEBUG: View 1 : 0.56050955414
+2016-08-24 09:36:50,418 DEBUG: View 2 : 0.426751592357
+2016-08-24 09:36:50,425 DEBUG: View 3 : 0.433121019108
+2016-08-24 09:36:50,498 DEBUG: Best view : Methyl_
+2016-08-24 09:36:51,225 DEBUG: Start: Iteration 13
+2016-08-24 09:36:51,242 DEBUG: View 0 : 0.420382165605
+2016-08-24 09:36:51,249 DEBUG: View 1 : 0.343949044586
+2016-08-24 09:36:51,285 DEBUG: View 2 : 0.573248407643
+2016-08-24 09:36:51,293 DEBUG: View 3 : 0.394904458599
+2016-08-24 09:36:51,367 DEBUG: Best view : RANSeq_
+2016-08-24 09:36:52,162 DEBUG: Start: Iteration 14
+2016-08-24 09:36:52,179 DEBUG: View 0 : 0.445859872611
+2016-08-24 09:36:52,187 DEBUG: View 1 : 0.566878980892
+2016-08-24 09:36:52,223 DEBUG: View 2 : 0.579617834395
+2016-08-24 09:36:52,230 DEBUG: View 3 : 0.541401273885
+2016-08-24 09:36:52,308 DEBUG: Best view : RANSeq_
+2016-08-24 09:36:53,175 DEBUG: Start: Iteration 15
+2016-08-24 09:36:53,191 DEBUG: View 0 : 0.624203821656
+2016-08-24 09:36:53,199 DEBUG: View 1 : 0.656050955414
+2016-08-24 09:36:53,235 DEBUG: View 2 : 0.592356687898
+2016-08-24 09:36:53,242 DEBUG: View 3 : 0.503184713376
+2016-08-24 09:36:53,321 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:54,247 DEBUG: Start: Iteration 16
+2016-08-24 09:36:54,263 DEBUG: View 0 : 0.636942675159
+2016-08-24 09:36:54,271 DEBUG: View 1 : 0.592356687898
+2016-08-24 09:36:54,307 DEBUG: View 2 : 0.554140127389
+2016-08-24 09:36:54,314 DEBUG: View 3 : 0.484076433121
+2016-08-24 09:36:54,396 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:55,378 DEBUG: Start: Iteration 17
+2016-08-24 09:36:55,395 DEBUG: View 0 : 0.458598726115
+2016-08-24 09:36:55,402 DEBUG: View 1 : 0.624203821656
+2016-08-24 09:36:55,439 DEBUG: View 2 : 0.426751592357
+2016-08-24 09:36:55,446 DEBUG: View 3 : 0.414012738854
+2016-08-24 09:36:55,529 DEBUG: Best view : MiRNA__
+2016-08-24 09:36:56,570 DEBUG: Start: Iteration 18
+2016-08-24 09:36:56,586 DEBUG: View 0 : 0.535031847134
+2016-08-24 09:36:56,594 DEBUG: View 1 : 0.343949044586
+2016-08-24 09:36:56,630 DEBUG: View 2 : 0.605095541401
+2016-08-24 09:36:56,638 DEBUG: View 3 : 0.496815286624
+2016-08-24 09:36:56,724 DEBUG: Best view : RANSeq_
+2016-08-24 09:36:57,833 DEBUG: Start: Iteration 19
+2016-08-24 09:36:57,850 DEBUG: View 0 : 0.426751592357
+2016-08-24 09:36:57,857 DEBUG: View 1 : 0.414012738854
+2016-08-24 09:36:57,893 DEBUG: View 2 : 0.433121019108
+2016-08-24 09:36:57,901 DEBUG: View 3 : 0.56050955414
+2016-08-24 09:36:57,989 DEBUG: Best view : Clinic_
+2016-08-24 09:36:59,153 DEBUG: Start: Iteration 20
+2016-08-24 09:36:59,170 DEBUG: View 0 : 0.40127388535
+2016-08-24 09:36:59,178 DEBUG: View 1 : 0.630573248408
+2016-08-24 09:36:59,214 DEBUG: View 2 : 0.477707006369
+2016-08-24 09:36:59,221 DEBUG: View 3 : 0.624203821656
+2016-08-24 09:36:59,312 DEBUG: Best view : Clinic_
+2016-08-24 09:37:00,535 DEBUG: Start: Iteration 21
+2016-08-24 09:37:00,552 DEBUG: View 0 : 0.566878980892
+2016-08-24 09:37:00,559 DEBUG: View 1 : 0.541401273885
+2016-08-24 09:37:00,595 DEBUG: View 2 : 0.509554140127
+2016-08-24 09:37:00,602 DEBUG: View 3 : 0.515923566879
+2016-08-24 09:37:00,695 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:01,976 DEBUG: Start: Iteration 22
+2016-08-24 09:37:01,992 DEBUG: View 0 : 0.452229299363
+2016-08-24 09:37:02,000 DEBUG: View 1 : 0.566878980892
+2016-08-24 09:37:02,036 DEBUG: View 2 : 0.433121019108
+2016-08-24 09:37:02,043 DEBUG: View 3 : 0.484076433121
+2016-08-24 09:37:02,137 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:03,474 DEBUG: Start: Iteration 23
+2016-08-24 09:37:03,490 DEBUG: View 0 : 0.573248407643
+2016-08-24 09:37:03,498 DEBUG: View 1 : 0.624203821656
+2016-08-24 09:37:03,534 DEBUG: View 2 : 0.503184713376
+2016-08-24 09:37:03,541 DEBUG: View 3 : 0.394904458599
+2016-08-24 09:37:03,638 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:05,032 DEBUG: Start: Iteration 24
+2016-08-24 09:37:05,048 DEBUG: View 0 : 0.605095541401
+2016-08-24 09:37:05,056 DEBUG: View 1 : 0.643312101911
+2016-08-24 09:37:05,092 DEBUG: View 2 : 0.630573248408
+2016-08-24 09:37:05,099 DEBUG: View 3 : 0.541401273885
+2016-08-24 09:37:05,197 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:06,651 DEBUG: Start: Iteration 25
+2016-08-24 09:37:06,668 DEBUG: View 0 : 0.43949044586
+2016-08-24 09:37:06,675 DEBUG: View 1 : 0.350318471338
+2016-08-24 09:37:06,711 DEBUG: View 2 : 0.414012738854
+2016-08-24 09:37:06,719 DEBUG: View 3 : 0.611464968153
+2016-08-24 09:37:06,819 DEBUG: Best view : Clinic_
+2016-08-24 09:37:08,325 DEBUG: Start: Iteration 26
+2016-08-24 09:37:08,342 DEBUG: View 0 : 0.43949044586
+2016-08-24 09:37:08,349 DEBUG: View 1 : 0.675159235669
+2016-08-24 09:37:08,385 DEBUG: View 2 : 0.585987261146
+2016-08-24 09:37:08,393 DEBUG: View 3 : 0.573248407643
+2016-08-24 09:37:08,496 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:10,064 DEBUG: Start: Iteration 27
+2016-08-24 09:37:10,080 DEBUG: View 0 : 0.433121019108
+2016-08-24 09:37:10,088 DEBUG: View 1 : 0.496815286624
+2016-08-24 09:37:10,124 DEBUG: View 2 : 0.496815286624
+2016-08-24 09:37:10,131 DEBUG: View 3 : 0.515923566879
+2016-08-24 09:37:10,237 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:11,867 DEBUG: Start: Iteration 28
+2016-08-24 09:37:11,883 DEBUG: View 0 : 0.522292993631
+2016-08-24 09:37:11,891 DEBUG: View 1 : 0.464968152866
+2016-08-24 09:37:11,927 DEBUG: View 2 : 0.452229299363
+2016-08-24 09:37:11,935 DEBUG: View 3 : 0.420382165605
+2016-08-24 09:37:12,042 DEBUG: Best view : Methyl_
+2016-08-24 09:37:13,729 DEBUG: Start: Iteration 29
+2016-08-24 09:37:13,746 DEBUG: View 0 : 0.764331210191
+2016-08-24 09:37:13,753 DEBUG: View 1 : 0.40127388535
+2016-08-24 09:37:13,789 DEBUG: View 2 : 0.40127388535
+2016-08-24 09:37:13,797 DEBUG: View 3 : 0.566878980892
+2016-08-24 09:37:13,907 DEBUG: Best view : Methyl_
+2016-08-24 09:37:15,653 DEBUG: Start: Iteration 30
+2016-08-24 09:37:15,669 DEBUG: View 0 : 0.522292993631
+2016-08-24 09:37:15,677 DEBUG: View 1 : 0.649681528662
+2016-08-24 09:37:15,713 DEBUG: View 2 : 0.426751592357
+2016-08-24 09:37:15,721 DEBUG: View 3 : 0.59872611465
+2016-08-24 09:37:15,834 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:17,639 DEBUG: Start: Iteration 31
+2016-08-24 09:37:17,655 DEBUG: View 0 : 0.605095541401
+2016-08-24 09:37:17,663 DEBUG: View 1 : 0.477707006369
+2016-08-24 09:37:17,699 DEBUG: View 2 : 0.388535031847
+2016-08-24 09:37:17,706 DEBUG: View 3 : 0.605095541401
+2016-08-24 09:37:17,820 DEBUG: Best view : Methyl_
+2016-08-24 09:37:19,683 DEBUG: Start: Iteration 32
+2016-08-24 09:37:19,699 DEBUG: View 0 : 0.579617834395
+2016-08-24 09:37:19,707 DEBUG: View 1 : 0.445859872611
+2016-08-24 09:37:19,743 DEBUG: View 2 : 0.464968152866
+2016-08-24 09:37:19,751 DEBUG: View 3 : 0.458598726115
+2016-08-24 09:37:19,868 DEBUG: Best view : Methyl_
+2016-08-24 09:37:21,795 DEBUG: Start: Iteration 33
+2016-08-24 09:37:21,811 DEBUG: View 0 : 0.630573248408
+2016-08-24 09:37:21,819 DEBUG: View 1 : 0.656050955414
+2016-08-24 09:37:21,855 DEBUG: View 2 : 0.617834394904
+2016-08-24 09:37:21,866 DEBUG: View 3 : 0.40127388535
+2016-08-24 09:37:21,984 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:23,972 DEBUG: Start: Iteration 34
+2016-08-24 09:37:23,989 DEBUG: View 0 : 0.585987261146
+2016-08-24 09:37:23,996 DEBUG: View 1 : 0.624203821656
+2016-08-24 09:37:24,033 DEBUG: View 2 : 0.56050955414
+2016-08-24 09:37:24,044 DEBUG: View 3 : 0.554140127389
+2016-08-24 09:37:24,164 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:26,207 DEBUG: Start: Iteration 35
+2016-08-24 09:37:26,223 DEBUG: View 0 : 0.515923566879
+2016-08-24 09:37:26,231 DEBUG: View 1 : 0.68152866242
+2016-08-24 09:37:26,267 DEBUG: View 2 : 0.369426751592
+2016-08-24 09:37:26,275 DEBUG: View 3 : 0.452229299363
+2016-08-24 09:37:26,397 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:28,497 DEBUG: Start: Iteration 36
+2016-08-24 09:37:28,513 DEBUG: View 0 : 0.503184713376
+2016-08-24 09:37:28,521 DEBUG: View 1 : 0.458598726115
+2016-08-24 09:37:28,557 DEBUG: View 2 : 0.528662420382
+2016-08-24 09:37:28,564 DEBUG: View 3 : 0.624203821656
+2016-08-24 09:37:28,689 DEBUG: Best view : Clinic_
+2016-08-24 09:37:30,849 DEBUG: Start: Iteration 37
+2016-08-24 09:37:30,866 DEBUG: View 0 : 0.630573248408
+2016-08-24 09:37:30,873 DEBUG: View 1 : 0.662420382166
+2016-08-24 09:37:30,910 DEBUG: View 2 : 0.414012738854
+2016-08-24 09:37:30,917 DEBUG: View 3 : 0.43949044586
+2016-08-24 09:37:31,044 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:33,257 DEBUG: Start: Iteration 38
+2016-08-24 09:37:33,273 DEBUG: View 0 : 0.414012738854
+2016-08-24 09:37:33,281 DEBUG: View 1 : 0.414012738854
+2016-08-24 09:37:33,316 DEBUG: View 2 : 0.471337579618
+2016-08-24 09:37:33,324 DEBUG: View 3 : 0.503184713376
+2016-08-24 09:37:33,453 DEBUG: Best view : Clinic_
+2016-08-24 09:37:35,720 DEBUG: Start: Iteration 39
+2016-08-24 09:37:35,736 DEBUG: View 0 : 0.375796178344
+2016-08-24 09:37:35,744 DEBUG: View 1 : 0.471337579618
+2016-08-24 09:37:35,780 DEBUG: View 2 : 0.585987261146
+2016-08-24 09:37:35,787 DEBUG: View 3 : 0.547770700637
+2016-08-24 09:37:35,923 DEBUG: Best view : RANSeq_
+2016-08-24 09:37:38,261 DEBUG: Start: Iteration 40
+2016-08-24 09:37:38,278 DEBUG: View 0 : 0.554140127389
+2016-08-24 09:37:38,286 DEBUG: View 1 : 0.528662420382
+2016-08-24 09:37:38,322 DEBUG: View 2 : 0.43949044586
+2016-08-24 09:37:38,329 DEBUG: View 3 : 0.515923566879
+2016-08-24 09:37:38,463 DEBUG: Best view : Methyl_
+2016-08-24 09:37:40,864 DEBUG: Start: Iteration 41
+2016-08-24 09:37:40,880 DEBUG: View 0 : 0.611464968153
+2016-08-24 09:37:40,888 DEBUG: View 1 : 0.675159235669
+2016-08-24 09:37:40,924 DEBUG: View 2 : 0.535031847134
+2016-08-24 09:37:40,931 DEBUG: View 3 : 0.471337579618
+2016-08-24 09:37:41,067 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:43,527 DEBUG: Start: Iteration 42
+2016-08-24 09:37:43,544 DEBUG: View 0 : 0.656050955414
+2016-08-24 09:37:43,552 DEBUG: View 1 : 0.522292993631
+2016-08-24 09:37:43,587 DEBUG: View 2 : 0.554140127389
+2016-08-24 09:37:43,595 DEBUG: View 3 : 0.617834394904
+2016-08-24 09:37:43,733 DEBUG: Best view : Methyl_
+2016-08-24 09:37:46,249 DEBUG: Start: Iteration 43
+2016-08-24 09:37:46,266 DEBUG: View 0 : 0.573248407643
+2016-08-24 09:37:46,274 DEBUG: View 1 : 0.31847133758
+2016-08-24 09:37:46,310 DEBUG: View 2 : 0.445859872611
+2016-08-24 09:37:46,317 DEBUG: View 3 : 0.573248407643
+2016-08-24 09:37:46,457 DEBUG: Best view : Methyl_
+2016-08-24 09:37:49,037 DEBUG: Start: Iteration 44
+2016-08-24 09:37:49,053 DEBUG: View 0 : 0.662420382166
+2016-08-24 09:37:49,061 DEBUG: View 1 : 0.656050955414
+2016-08-24 09:37:49,097 DEBUG: View 2 : 0.509554140127
+2016-08-24 09:37:49,104 DEBUG: View 3 : 0.433121019108
+2016-08-24 09:37:49,246 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:51,883 DEBUG: Start: Iteration 45
+2016-08-24 09:37:51,900 DEBUG: View 0 : 0.630573248408
+2016-08-24 09:37:51,908 DEBUG: View 1 : 0.649681528662
+2016-08-24 09:37:51,943 DEBUG: View 2 : 0.452229299363
+2016-08-24 09:37:51,951 DEBUG: View 3 : 0.566878980892
+2016-08-24 09:37:52,096 DEBUG: Best view : MiRNA__
+2016-08-24 09:37:54,788 DEBUG: Start: Iteration 46
+2016-08-24 09:37:54,804 DEBUG: View 0 : 0.426751592357
+2016-08-24 09:37:54,812 DEBUG: View 1 : 0.471337579618
+2016-08-24 09:37:54,848 DEBUG: View 2 : 0.509554140127
+2016-08-24 09:37:54,855 DEBUG: View 3 : 0.585987261146
+2016-08-24 09:37:55,001 DEBUG: Best view : Clinic_
+2016-08-24 09:37:57,748 DEBUG: Start: Iteration 47
+2016-08-24 09:37:57,764 DEBUG: View 0 : 0.503184713376
+2016-08-24 09:37:57,772 DEBUG: View 1 : 0.40127388535
+2016-08-24 09:37:57,808 DEBUG: View 2 : 0.464968152866
+2016-08-24 09:37:57,815 DEBUG: View 3 : 0.43949044586
+2016-08-24 09:37:57,963 DEBUG: Best view : Methyl_
+2016-08-24 09:38:00,821 DEBUG: Start: Iteration 48
+2016-08-24 09:38:00,837 DEBUG: View 0 : 0.687898089172
+2016-08-24 09:38:00,845 DEBUG: View 1 : 0.726114649682
+2016-08-24 09:38:00,883 DEBUG: View 2 : 0.503184713376
+2016-08-24 09:38:00,891 DEBUG: View 3 : 0.630573248408
+2016-08-24 09:38:01,052 DEBUG: Best view : MiRNA__
+2016-08-24 09:38:04,075 DEBUG: Start: Iteration 49
+2016-08-24 09:38:04,092 DEBUG: View 0 : 0.496815286624
+2016-08-24 09:38:04,099 DEBUG: View 1 : 0.426751592357
+2016-08-24 09:38:04,135 DEBUG: View 2 : 0.420382165605
+2016-08-24 09:38:04,142 DEBUG: View 3 : 0.426751592357
+2016-08-24 09:38:04,142 WARNING: All bad for iteration 48
+2016-08-24 09:38:04,297 DEBUG: Best view : Methyl_
+2016-08-24 09:38:07,226 DEBUG: Start: Iteration 50
+2016-08-24 09:38:07,243 DEBUG: View 0 : 0.630573248408
+2016-08-24 09:38:07,250 DEBUG: View 1 : 0.777070063694
+2016-08-24 09:38:07,286 DEBUG: View 2 : 0.464968152866
+2016-08-24 09:38:07,294 DEBUG: View 3 : 0.605095541401
+2016-08-24 09:38:07,449 DEBUG: Best view : MiRNA__
+2016-08-24 09:38:10,439 DEBUG: Start: Iteration 51
+2016-08-24 09:38:10,456 DEBUG: View 0 : 0.757961783439
+2016-08-24 09:38:10,464 DEBUG: View 1 : 0.490445859873
+2016-08-24 09:38:10,499 DEBUG: View 2 : 0.464968152866
+2016-08-24 09:38:10,507 DEBUG: View 3 : 0.509554140127
+2016-08-24 09:38:10,664 DEBUG: Best view : Methyl_
+2016-08-24 09:38:13,867 DEBUG: Start: Iteration 52
+2016-08-24 09:38:13,885 DEBUG: View 0 : 0.496815286624
+2016-08-24 09:38:13,892 DEBUG: View 1 : 0.59872611465
+2016-08-24 09:38:13,928 DEBUG: View 2 : 0.407643312102
+2016-08-24 09:38:13,936 DEBUG: View 3 : 0.585987261146
+2016-08-24 09:38:14,100 DEBUG: Best view : MiRNA__
+2016-08-24 09:38:17,221 INFO: Start: Classification
+2016-08-24 09:38:24,786 INFO: Done: Fold number 2
+2016-08-24 09:38:24,786 INFO: Done: Classification
+2016-08-24 09:38:24,786 INFO: Info: Time for Classification: 269[s]
+2016-08-24 09:38:24,786 INFO: Start: Result Analysis for Mumbo
+2016-08-24 09:38:42,191 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 74.1078719582
+ -On Test : 79.0983606557
+ -On Validation : 81.5533980583
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.0075 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.007 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.0075 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0274615384615
+ - Percentage of time chosen : 0.96
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0292820512821
+ - Percentage of time chosen : 0.028
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0261987179487
+ - Percentage of time chosen : 0.004
+ - On Clinic_ :
+ - Mean average Accuracy : 0.027391025641
+ - Percentage of time chosen : 0.008
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0279617834395
+ - Percentage of time chosen : 0.961
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.028178343949
+ - Percentage of time chosen : 0.026
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0253566878981
+ - Percentage of time chosen : 0.005
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0265031847134
+ - Percentage of time chosen : 0.008
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 66.6666666667
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 64.9681528662
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 65.8174097665
+ Accuracy on test : 71.7213114754
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 66.6666666667
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 72.8155339806
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 64.9681528662
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 65.8174097665
+ Accuracy on test : 71.7213114754
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 56.4102564103
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 66.0194174757
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 63.0573248408
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 76.6990291262
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 59.7337906255
+ Accuracy on test : 69.262295082
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 67.9611650485
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 72.8155339806
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.904540258
+ Accuracy on test : 72.9508196721
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 65.3846153846
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 72.8155339806
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 63.5840274375
+ Accuracy on test : 72.9508196721
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 68.5897435897
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 63.6942675159
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 72.8155339806
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 66.1420055528
+ Accuracy on test : 75.8196721311
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 68.8524590164
+ Accuracy on validation : 71.8446601942
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.4203821656
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 64.2230115956
+ Accuracy on test : 71.3114754098
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 73.0769230769
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 75.7281553398
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 62.4203821656
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 72.8155339806
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.7486526213
+ Accuracy on test : 75.4098360656
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 73.7179487179
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 78.640776699
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 65.6050955414
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 71.8446601942
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.6615221297
+ Accuracy on test : 77.0491803279
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 71.7948717949
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 65.6050955414
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 71.8446601942
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 68.6999836681
+ Accuracy on test : 77.4590163934
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 69.8717948718
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 71.3375796178
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 70.6046872448
+ Accuracy on test : 77.868852459
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 69.8717948718
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 76.6990291262
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.4267515924
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 69.6492732321
+ Accuracy on test : 76.6393442623
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 69.8717948718
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 70.7006369427
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 70.2862159072
+ Accuracy on test : 76.6393442623
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 70.5128205128
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 68.7898089172
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.651314715
+ Accuracy on test : 78.6885245902
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 68.5897435897
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 73.2484076433
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.9190756165
+ Accuracy on test : 77.868852459
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 67.3076923077
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 76.6990291262
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 66.8789808917
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 67.0933365997
+ Accuracy on test : 77.4590163934
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 62.8205128205
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 67.5159235669
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 65.1682181937
+ Accuracy on test : 76.2295081967
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 68.7898089172
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.4077249714
+ Accuracy on test : 77.0491803279
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 68.5897435897
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.4158909032
+ Accuracy on test : 78.2786885246
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 71.7948717949
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 76.6990291262
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.0184550057
+ Accuracy on test : 78.2786885246
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 73.7179487179
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 68.152866242
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.93540748
+ Accuracy on test : 79.9180327869
+ - Iteration 23
+ Fold 1
+ Accuracy on train : 71.7948717949
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.0184550057
+ Accuracy on test : 78.6885245902
+ - Iteration 24
+ Fold 1
+ Accuracy on train : 74.358974359
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 65.6050955414
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.9820349502
+ Accuracy on test : 79.9180327869
+ - Iteration 25
+ Fold 1
+ Accuracy on train : 74.358974359
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 64.9681528662
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 72.8155339806
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 69.6635636126
+ Accuracy on test : 80.3278688525
+ - Iteration 26
+ Fold 1
+ Accuracy on train : 78.2051282051
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 67.5159235669
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 72.860525886
+ Accuracy on test : 80.3278688525
+ - Iteration 27
+ Fold 1
+ Accuracy on train : 74.358974359
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 81.5533980583
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 67.5159235669
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.9374489629
+ Accuracy on test : 79.9180327869
+ - Iteration 28
+ Fold 1
+ Accuracy on train : 75.641025641
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 82.5242718447
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 67.5159235669
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 71.578474604
+ Accuracy on test : 80.3278688525
+ - Iteration 29
+ Fold 1
+ Accuracy on train : 73.7179487179
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 68.7898089172
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 75.7281553398
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 71.2538788176
+ Accuracy on test : 79.5081967213
+ - Iteration 30
+ Fold 1
+ Accuracy on train : 71.1538461538
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 78.640776699
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 71.3375796178
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 71.2457128858
+ Accuracy on test : 80.3278688525
+ - Iteration 31
+ Fold 1
+ Accuracy on train : 75.0
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 81.5533980583
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 73.2484076433
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 78.640776699
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 74.1242038217
+ Accuracy on test : 81.5573770492
+ - Iteration 32
+ Fold 1
+ Accuracy on train : 75.641025641
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 81.5533980583
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 75.1592356688
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 75.4001306549
+ Accuracy on test : 81.1475409836
+ - Iteration 33
+ Fold 1
+ Accuracy on train : 74.358974359
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 81.5533980583
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 71.974522293
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 73.166748326
+ Accuracy on test : 79.9180327869
+ - Iteration 34
+ Fold 1
+ Accuracy on train : 71.1538461538
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 71.3375796178
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 71.2457128858
+ Accuracy on test : 79.5081967213
+ - Iteration 35
+ Fold 1
+ Accuracy on train : 73.7179487179
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 71.974522293
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 72.8462355055
+ Accuracy on test : 79.5081967213
+ - Iteration 36
+ Fold 1
+ Accuracy on train : 72.4358974359
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+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 976
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 977
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 978
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 979
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 980
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 981
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 982
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 983
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 984
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 985
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 986
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 987
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 988
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 989
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:02:40 0:00:07
+ Fold 2 0:04:22 0:00:07
+ Total 0:07:02 0:00:15
+ So a total classification time of 0:04:29.
+
+
+2016-08-24 09:38:43,134 INFO: Done: Result Analysis
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093842Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093842Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..50c8876ea3458bb044bb4ed265a50cce6ac905b0
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093842Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093842Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093842Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6a91f6d691bc3e2c7009838126628a0ae2baafd8
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-093842Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
@@ -0,0 +1,14060 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 74.1078719582
+ -On Test : 79.0983606557
+ -On Validation : 81.5533980583
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.0075 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.007 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.0075 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0274615384615
+ - Percentage of time chosen : 0.96
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0292820512821
+ - Percentage of time chosen : 0.028
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0261987179487
+ - Percentage of time chosen : 0.004
+ - On Clinic_ :
+ - Mean average Accuracy : 0.027391025641
+ - Percentage of time chosen : 0.008
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0279617834395
+ - Percentage of time chosen : 0.961
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.028178343949
+ - Percentage of time chosen : 0.026
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0253566878981
+ - Percentage of time chosen : 0.005
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0265031847134
+ - Percentage of time chosen : 0.008
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 66.6666666667
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 64.9681528662
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 65.8174097665
+ Accuracy on test : 71.7213114754
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 66.6666666667
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 72.8155339806
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 64.9681528662
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 65.8174097665
+ Accuracy on test : 71.7213114754
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 56.4102564103
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 66.0194174757
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 63.0573248408
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 76.6990291262
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 59.7337906255
+ Accuracy on test : 69.262295082
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 67.9611650485
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 72.8155339806
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 63.904540258
+ Accuracy on test : 72.9508196721
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 65.3846153846
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 72.8155339806
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 63.5840274375
+ Accuracy on test : 72.9508196721
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 68.5897435897
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 63.6942675159
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 72.8155339806
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 66.1420055528
+ Accuracy on test : 75.8196721311
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 68.8524590164
+ Accuracy on validation : 71.8446601942
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 62.4203821656
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 64.2230115956
+ Accuracy on test : 71.3114754098
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 73.0769230769
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 75.7281553398
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 62.4203821656
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 72.8155339806
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.7486526213
+ Accuracy on test : 75.4098360656
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 73.7179487179
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 78.640776699
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 65.6050955414
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 71.8446601942
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.6615221297
+ Accuracy on test : 77.0491803279
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 71.7948717949
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 65.6050955414
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 71.8446601942
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 68.6999836681
+ Accuracy on test : 77.4590163934
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 69.8717948718
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 71.3375796178
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 70.6046872448
+ Accuracy on test : 77.868852459
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 69.8717948718
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 76.6990291262
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.4267515924
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 69.6492732321
+ Accuracy on test : 76.6393442623
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 69.8717948718
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 70.7006369427
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 70.2862159072
+ Accuracy on test : 76.6393442623
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 70.5128205128
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 68.7898089172
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 69.651314715
+ Accuracy on test : 78.6885245902
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 68.5897435897
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 73.2484076433
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.9190756165
+ Accuracy on test : 77.868852459
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 67.3076923077
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 76.6990291262
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 66.8789808917
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 67.0933365997
+ Accuracy on test : 77.4590163934
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 62.8205128205
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 67.5159235669
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 76.6990291262
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 65.1682181937
+ Accuracy on test : 76.2295081967
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 68.7898089172
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.4077249714
+ Accuracy on test : 77.0491803279
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 68.5897435897
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 66.2420382166
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
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+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
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+ Accuracy on test : 72.9508196721
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+ Accuracy on train : 61.7834394904
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+ - Iteration 997
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+ Accuracy on test : 72.9508196721
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+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
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+ Accuracy on test : 72.9508196721
+ - Iteration 998
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+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
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+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.7834394904
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.6609505145
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:02:40 0:00:07
+ Fold 2 0:04:22 0:00:07
+ Total 0:07:02 0:00:15
+ So a total classification time of 0:04:29.
+
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-094408-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-094408-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..f87aee135296c70980613b7e93a00eec9b073189
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-094408-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,531 @@
+2016-08-24 09:44:08,361 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:44:08,361 INFO: Info: Labels used: No, Yes
+2016-08-24 09:44:08,361 INFO: Info: Length of dataset:347
+2016-08-24 09:44:08,363 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:44:08,363 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:44:08,363 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:44:08,364 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:44:08,364 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:44:08,365 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:44:08,365 INFO: Done: Read Database Files
+2016-08-24 09:44:08,365 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:44:08,368 INFO: Done: Determine validation split
+2016-08-24 09:44:08,368 INFO: Start: Determine 2 folds
+2016-08-24 09:44:08,378 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:44:08,378 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:44:08,378 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:44:08,379 INFO: Done: Determine folds
+2016-08-24 09:44:08,379 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:44:08,379 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:44:08,379 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:44:15,803 DEBUG: 0.585648414986Poulet
+2016-08-24 09:44:15,803 DEBUG: 0.560864553314Poulet
+2016-08-24 09:44:15,803 DEBUG: 0.511642651297Poulet
+2016-08-24 09:44:15,803 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:44:15,804 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:44:17,725 DEBUG: 0.543054755043Poulet
+2016-08-24 09:44:17,725 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:44:17,725 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:44:34,897 DEBUG: 0.577463976945Poulet
+2016-08-24 09:44:34,898 DEBUG: 0.563400576369Poulet
+2016-08-24 09:44:34,898 DEBUG: 0.511930835735Poulet
+2016-08-24 09:44:34,899 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:44:34,899 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:44:36,702 DEBUG: 0.56265129683Poulet
+2016-08-24 09:44:36,702 DEBUG: 0.561383285303Poulet
+2016-08-24 09:44:36,702 DEBUG: 0.501844380403Poulet
+2016-08-24 09:44:36,702 DEBUG: 0.514351585014Poulet
+2016-08-24 09:44:36,702 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:44:36,703 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:45:24,687 DEBUG: 0.541556195965Poulet
+2016-08-24 09:45:24,687 DEBUG: 0.528357348703Poulet
+2016-08-24 09:45:24,689 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:45:24,689 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:45:24,689 INFO: Start: Fold number 1
+2016-08-24 09:45:26,374 DEBUG: Start: Iteration 1
+2016-08-24 09:45:26,392 DEBUG: View 0 : 0.379746835443
+2016-08-24 09:45:26,400 DEBUG: View 1 : 0.620253164557
+2016-08-24 09:45:26,431 DEBUG: View 2 : 0.620253164557
+2016-08-24 09:45:26,442 DEBUG: View 3 : 0.620253164557
+2016-08-24 09:45:26,485 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:26,561 DEBUG: Start: Iteration 2
+2016-08-24 09:45:26,579 DEBUG: View 0 : 0.443037974684
+2016-08-24 09:45:26,587 DEBUG: View 1 : 0.563291139241
+2016-08-24 09:45:26,628 DEBUG: View 2 : 0.563291139241
+2016-08-24 09:45:26,636 DEBUG: View 3 : 0.651898734177
+2016-08-24 09:45:26,693 DEBUG: Best view : Clinic_
+2016-08-24 09:45:26,830 DEBUG: Start: Iteration 3
+2016-08-24 09:45:26,847 DEBUG: View 0 : 0.550632911392
+2016-08-24 09:45:26,855 DEBUG: View 1 : 0.563291139241
+2016-08-24 09:45:26,892 DEBUG: View 2 : 0.53164556962
+2016-08-24 09:45:26,902 DEBUG: View 3 : 0.462025316456
+2016-08-24 09:45:26,957 DEBUG: Best view : Clinic_
+2016-08-24 09:45:27,145 DEBUG: Start: Iteration 4
+2016-08-24 09:45:27,161 DEBUG: View 0 : 0.569620253165
+2016-08-24 09:45:27,169 DEBUG: View 1 : 0.329113924051
+2016-08-24 09:45:27,206 DEBUG: View 2 : 0.525316455696
+2016-08-24 09:45:27,214 DEBUG: View 3 : 0.588607594937
+2016-08-24 09:45:27,272 DEBUG: Best view : Clinic_
+2016-08-24 09:45:27,520 DEBUG: Start: Iteration 5
+2016-08-24 09:45:27,537 DEBUG: View 0 : 0.443037974684
+2016-08-24 09:45:27,545 DEBUG: View 1 : 0.569620253165
+2016-08-24 09:45:27,582 DEBUG: View 2 : 0.537974683544
+2016-08-24 09:45:27,590 DEBUG: View 3 : 0.518987341772
+2016-08-24 09:45:27,648 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:27,951 DEBUG: Start: Iteration 6
+2016-08-24 09:45:27,968 DEBUG: View 0 : 0.386075949367
+2016-08-24 09:45:27,976 DEBUG: View 1 : 0.651898734177
+2016-08-24 09:45:28,012 DEBUG: View 2 : 0.430379746835
+2016-08-24 09:45:28,020 DEBUG: View 3 : 0.443037974684
+2016-08-24 09:45:28,080 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:28,444 DEBUG: Start: Iteration 7
+2016-08-24 09:45:28,460 DEBUG: View 0 : 0.664556962025
+2016-08-24 09:45:28,468 DEBUG: View 1 : 0.443037974684
+2016-08-24 09:45:28,505 DEBUG: View 2 : 0.525316455696
+2016-08-24 09:45:28,512 DEBUG: View 3 : 0.487341772152
+2016-08-24 09:45:28,575 DEBUG: Best view : Methyl_
+2016-08-24 09:45:28,997 DEBUG: Start: Iteration 8
+2016-08-24 09:45:29,014 DEBUG: View 0 : 0.424050632911
+2016-08-24 09:45:29,021 DEBUG: View 1 : 0.417721518987
+2016-08-24 09:45:29,058 DEBUG: View 2 : 0.556962025316
+2016-08-24 09:45:29,066 DEBUG: View 3 : 0.594936708861
+2016-08-24 09:45:29,131 DEBUG: Best view : Clinic_
+2016-08-24 09:45:29,628 DEBUG: Start: Iteration 9
+2016-08-24 09:45:29,645 DEBUG: View 0 : 0.512658227848
+2016-08-24 09:45:29,653 DEBUG: View 1 : 0.417721518987
+2016-08-24 09:45:29,691 DEBUG: View 2 : 0.639240506329
+2016-08-24 09:45:29,699 DEBUG: View 3 : 0.411392405063
+2016-08-24 09:45:29,769 DEBUG: Best view : RANSeq_
+2016-08-24 09:45:30,333 DEBUG: Start: Iteration 10
+2016-08-24 09:45:30,349 DEBUG: View 0 : 0.506329113924
+2016-08-24 09:45:30,357 DEBUG: View 1 : 0.639240506329
+2016-08-24 09:45:30,394 DEBUG: View 2 : 0.424050632911
+2016-08-24 09:45:30,402 DEBUG: View 3 : 0.436708860759
+2016-08-24 09:45:30,471 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:31,083 DEBUG: Start: Iteration 11
+2016-08-24 09:45:31,100 DEBUG: View 0 : 0.626582278481
+2016-08-24 09:45:31,107 DEBUG: View 1 : 0.354430379747
+2016-08-24 09:45:31,144 DEBUG: View 2 : 0.398734177215
+2016-08-24 09:45:31,152 DEBUG: View 3 : 0.607594936709
+2016-08-24 09:45:31,223 DEBUG: Best view : Methyl_
+2016-08-24 09:45:31,904 DEBUG: Start: Iteration 12
+2016-08-24 09:45:31,921 DEBUG: View 0 : 0.689873417722
+2016-08-24 09:45:31,929 DEBUG: View 1 : 0.481012658228
+2016-08-24 09:45:31,965 DEBUG: View 2 : 0.46835443038
+2016-08-24 09:45:31,973 DEBUG: View 3 : 0.493670886076
+2016-08-24 09:45:32,047 DEBUG: Best view : Methyl_
+2016-08-24 09:45:32,812 DEBUG: Start: Iteration 13
+2016-08-24 09:45:32,829 DEBUG: View 0 : 0.417721518987
+2016-08-24 09:45:32,837 DEBUG: View 1 : 0.639240506329
+2016-08-24 09:45:32,874 DEBUG: View 2 : 0.405063291139
+2016-08-24 09:45:32,882 DEBUG: View 3 : 0.620253164557
+2016-08-24 09:45:32,957 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:33,749 DEBUG: Start: Iteration 14
+2016-08-24 09:45:33,765 DEBUG: View 0 : 0.481012658228
+2016-08-24 09:45:33,773 DEBUG: View 1 : 0.278481012658
+2016-08-24 09:45:33,809 DEBUG: View 2 : 0.379746835443
+2016-08-24 09:45:33,817 DEBUG: View 3 : 0.392405063291
+2016-08-24 09:45:33,818 WARNING: WARNING: All bad for iteration 13
+2016-08-24 09:45:33,896 DEBUG: Best view : Methyl_
+2016-08-24 09:45:34,783 DEBUG: Start: Iteration 15
+2016-08-24 09:45:34,801 DEBUG: View 0 : 0.436708860759
+2016-08-24 09:45:34,809 DEBUG: View 1 : 0.563291139241
+2016-08-24 09:45:34,849 DEBUG: View 2 : 0.544303797468
+2016-08-24 09:45:34,858 DEBUG: View 3 : 0.474683544304
+2016-08-24 09:45:34,952 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:35,984 DEBUG: Start: Iteration 16
+2016-08-24 09:45:36,002 DEBUG: View 0 : 0.550632911392
+2016-08-24 09:45:36,010 DEBUG: View 1 : 0.443037974684
+2016-08-24 09:45:36,049 DEBUG: View 2 : 0.544303797468
+2016-08-24 09:45:36,057 DEBUG: View 3 : 0.506329113924
+2016-08-24 09:45:36,141 DEBUG: Best view : RANSeq_
+2016-08-24 09:45:37,137 DEBUG: Start: Iteration 17
+2016-08-24 09:45:37,154 DEBUG: View 0 : 0.392405063291
+2016-08-24 09:45:37,162 DEBUG: View 1 : 0.670886075949
+2016-08-24 09:45:37,199 DEBUG: View 2 : 0.443037974684
+2016-08-24 09:45:37,207 DEBUG: View 3 : 0.398734177215
+2016-08-24 09:45:37,294 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:38,383 DEBUG: Start: Iteration 18
+2016-08-24 09:45:38,400 DEBUG: View 0 : 0.462025316456
+2016-08-24 09:45:38,407 DEBUG: View 1 : 0.620253164557
+2016-08-24 09:45:38,444 DEBUG: View 2 : 0.493670886076
+2016-08-24 09:45:38,452 DEBUG: View 3 : 0.556962025316
+2016-08-24 09:45:38,541 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:39,640 DEBUG: Start: Iteration 19
+2016-08-24 09:45:39,656 DEBUG: View 0 : 0.689873417722
+2016-08-24 09:45:39,664 DEBUG: View 1 : 0.544303797468
+2016-08-24 09:45:39,701 DEBUG: View 2 : 0.594936708861
+2016-08-24 09:45:39,708 DEBUG: View 3 : 0.594936708861
+2016-08-24 09:45:39,799 DEBUG: Best view : Methyl_
+2016-08-24 09:45:40,989 DEBUG: Start: Iteration 20
+2016-08-24 09:45:41,005 DEBUG: View 0 : 0.550632911392
+2016-08-24 09:45:41,013 DEBUG: View 1 : 0.613924050633
+2016-08-24 09:45:41,050 DEBUG: View 2 : 0.613924050633
+2016-08-24 09:45:41,058 DEBUG: View 3 : 0.607594936709
+2016-08-24 09:45:41,151 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:42,389 DEBUG: Start: Iteration 21
+2016-08-24 09:45:42,405 DEBUG: View 0 : 0.651898734177
+2016-08-24 09:45:42,413 DEBUG: View 1 : 0.664556962025
+2016-08-24 09:45:42,450 DEBUG: View 2 : 0.563291139241
+2016-08-24 09:45:42,458 DEBUG: View 3 : 0.417721518987
+2016-08-24 09:45:42,554 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:43,837 DEBUG: Start: Iteration 22
+2016-08-24 09:45:43,853 DEBUG: View 0 : 0.537974683544
+2016-08-24 09:45:43,861 DEBUG: View 1 : 0.607594936709
+2016-08-24 09:45:43,899 DEBUG: View 2 : 0.582278481013
+2016-08-24 09:45:43,906 DEBUG: View 3 : 0.493670886076
+2016-08-24 09:45:44,006 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:45,380 DEBUG: Start: Iteration 23
+2016-08-24 09:45:45,397 DEBUG: View 0 : 0.626582278481
+2016-08-24 09:45:45,405 DEBUG: View 1 : 0.462025316456
+2016-08-24 09:45:45,443 DEBUG: View 2 : 0.613924050633
+2016-08-24 09:45:45,451 DEBUG: View 3 : 0.487341772152
+2016-08-24 09:45:45,552 DEBUG: Best view : Methyl_
+2016-08-24 09:45:46,972 DEBUG: Start: Iteration 24
+2016-08-24 09:45:46,991 DEBUG: View 0 : 0.474683544304
+2016-08-24 09:45:46,999 DEBUG: View 1 : 0.607594936709
+2016-08-24 09:45:47,037 DEBUG: View 2 : 0.556962025316
+2016-08-24 09:45:47,045 DEBUG: View 3 : 0.405063291139
+2016-08-24 09:45:47,149 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:48,783 DEBUG: Start: Iteration 25
+2016-08-24 09:45:48,799 DEBUG: View 0 : 0.5
+2016-08-24 09:45:48,807 DEBUG: View 1 : 0.512658227848
+2016-08-24 09:45:48,844 DEBUG: View 2 : 0.487341772152
+2016-08-24 09:45:48,852 DEBUG: View 3 : 0.474683544304
+2016-08-24 09:45:48,956 DEBUG: Best view : Methyl_
+2016-08-24 09:45:50,533 DEBUG: Start: Iteration 26
+2016-08-24 09:45:50,550 DEBUG: View 0 : 0.645569620253
+2016-08-24 09:45:50,558 DEBUG: View 1 : 0.651898734177
+2016-08-24 09:45:50,595 DEBUG: View 2 : 0.411392405063
+2016-08-24 09:45:50,603 DEBUG: View 3 : 0.582278481013
+2016-08-24 09:45:50,707 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:52,409 DEBUG: Start: Iteration 27
+2016-08-24 09:45:52,430 DEBUG: View 0 : 0.588607594937
+2016-08-24 09:45:52,439 DEBUG: View 1 : 0.601265822785
+2016-08-24 09:45:52,483 DEBUG: View 2 : 0.588607594937
+2016-08-24 09:45:52,492 DEBUG: View 3 : 0.449367088608
+2016-08-24 09:45:52,615 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:54,284 DEBUG: Start: Iteration 28
+2016-08-24 09:45:54,301 DEBUG: View 0 : 0.46835443038
+2016-08-24 09:45:54,309 DEBUG: View 1 : 0.405063291139
+2016-08-24 09:45:54,345 DEBUG: View 2 : 0.455696202532
+2016-08-24 09:45:54,353 DEBUG: View 3 : 0.436708860759
+2016-08-24 09:45:54,354 WARNING: WARNING: All bad for iteration 27
+2016-08-24 09:45:54,463 DEBUG: Best view : Methyl_
+2016-08-24 09:45:56,154 DEBUG: Start: Iteration 29
+2016-08-24 09:45:56,170 DEBUG: View 0 : 0.405063291139
+2016-08-24 09:45:56,178 DEBUG: View 1 : 0.632911392405
+2016-08-24 09:45:56,214 DEBUG: View 2 : 0.417721518987
+2016-08-24 09:45:56,222 DEBUG: View 3 : 0.474683544304
+2016-08-24 09:45:56,334 DEBUG: Best view : MiRNA__
+2016-08-24 09:45:58,088 DEBUG: Start: Iteration 30
+2016-08-24 09:45:58,104 DEBUG: View 0 : 0.5
+2016-08-24 09:45:58,112 DEBUG: View 1 : 0.398734177215
+2016-08-24 09:45:58,149 DEBUG: View 2 : 0.455696202532
+2016-08-24 09:45:58,157 DEBUG: View 3 : 0.417721518987
+2016-08-24 09:45:58,270 DEBUG: Best view : Methyl_
+2016-08-24 09:46:00,083 DEBUG: Start: Iteration 31
+2016-08-24 09:46:00,100 DEBUG: View 0 : 0.462025316456
+2016-08-24 09:46:00,108 DEBUG: View 1 : 0.424050632911
+2016-08-24 09:46:00,144 DEBUG: View 2 : 0.417721518987
+2016-08-24 09:46:00,152 DEBUG: View 3 : 0.436708860759
+2016-08-24 09:46:00,152 WARNING: WARNING: All bad for iteration 30
+2016-08-24 09:46:00,269 DEBUG: Best view : Methyl_
+2016-08-24 09:46:02,316 DEBUG: Start: Iteration 32
+2016-08-24 09:46:02,332 DEBUG: View 0 : 0.632911392405
+2016-08-24 09:46:02,340 DEBUG: View 1 : 0.727848101266
+2016-08-24 09:46:02,377 DEBUG: View 2 : 0.626582278481
+2016-08-24 09:46:02,385 DEBUG: View 3 : 0.449367088608
+2016-08-24 09:46:02,504 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:04,444 DEBUG: Start: Iteration 33
+2016-08-24 09:46:04,461 DEBUG: View 0 : 0.556962025316
+2016-08-24 09:46:04,469 DEBUG: View 1 : 0.626582278481
+2016-08-24 09:46:04,505 DEBUG: View 2 : 0.506329113924
+2016-08-24 09:46:04,513 DEBUG: View 3 : 0.525316455696
+2016-08-24 09:46:04,633 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:06,628 DEBUG: Start: Iteration 34
+2016-08-24 09:46:06,645 DEBUG: View 0 : 0.53164556962
+2016-08-24 09:46:06,652 DEBUG: View 1 : 0.506329113924
+2016-08-24 09:46:06,689 DEBUG: View 2 : 0.430379746835
+2016-08-24 09:46:06,697 DEBUG: View 3 : 0.481012658228
+2016-08-24 09:46:06,820 DEBUG: Best view : Methyl_
+2016-08-24 09:46:08,877 DEBUG: Start: Iteration 35
+2016-08-24 09:46:08,894 DEBUG: View 0 : 0.430379746835
+2016-08-24 09:46:08,901 DEBUG: View 1 : 0.544303797468
+2016-08-24 09:46:08,938 DEBUG: View 2 : 0.474683544304
+2016-08-24 09:46:08,945 DEBUG: View 3 : 0.405063291139
+2016-08-24 09:46:09,070 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:11,182 DEBUG: Start: Iteration 36
+2016-08-24 09:46:11,198 DEBUG: View 0 : 0.569620253165
+2016-08-24 09:46:11,206 DEBUG: View 1 : 0.664556962025
+2016-08-24 09:46:11,243 DEBUG: View 2 : 0.651898734177
+2016-08-24 09:46:11,251 DEBUG: View 3 : 0.594936708861
+2016-08-24 09:46:11,378 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:13,547 DEBUG: Start: Iteration 37
+2016-08-24 09:46:13,563 DEBUG: View 0 : 0.474683544304
+2016-08-24 09:46:13,571 DEBUG: View 1 : 0.651898734177
+2016-08-24 09:46:13,607 DEBUG: View 2 : 0.392405063291
+2016-08-24 09:46:13,615 DEBUG: View 3 : 0.392405063291
+2016-08-24 09:46:13,744 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:15,973 DEBUG: Start: Iteration 38
+2016-08-24 09:46:15,989 DEBUG: View 0 : 0.651898734177
+2016-08-24 09:46:15,997 DEBUG: View 1 : 0.639240506329
+2016-08-24 09:46:16,034 DEBUG: View 2 : 0.487341772152
+2016-08-24 09:46:16,042 DEBUG: View 3 : 0.582278481013
+2016-08-24 09:46:16,175 DEBUG: Best view : Methyl_
+2016-08-24 09:46:18,469 DEBUG: Start: Iteration 39
+2016-08-24 09:46:18,485 DEBUG: View 0 : 0.537974683544
+2016-08-24 09:46:18,493 DEBUG: View 1 : 0.392405063291
+2016-08-24 09:46:18,529 DEBUG: View 2 : 0.525316455696
+2016-08-24 09:46:18,537 DEBUG: View 3 : 0.46835443038
+2016-08-24 09:46:18,671 DEBUG: Best view : Methyl_
+2016-08-24 09:46:21,024 DEBUG: Start: Iteration 40
+2016-08-24 09:46:21,041 DEBUG: View 0 : 0.639240506329
+2016-08-24 09:46:21,049 DEBUG: View 1 : 0.582278481013
+2016-08-24 09:46:21,085 DEBUG: View 2 : 0.474683544304
+2016-08-24 09:46:21,093 DEBUG: View 3 : 0.481012658228
+2016-08-24 09:46:21,229 DEBUG: Best view : Methyl_
+2016-08-24 09:46:23,647 DEBUG: Start: Iteration 41
+2016-08-24 09:46:23,663 DEBUG: View 0 : 0.481012658228
+2016-08-24 09:46:23,671 DEBUG: View 1 : 0.664556962025
+2016-08-24 09:46:23,708 DEBUG: View 2 : 0.5
+2016-08-24 09:46:23,715 DEBUG: View 3 : 0.392405063291
+2016-08-24 09:46:23,854 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:26,328 DEBUG: Start: Iteration 42
+2016-08-24 09:46:26,345 DEBUG: View 0 : 0.506329113924
+2016-08-24 09:46:26,352 DEBUG: View 1 : 0.582278481013
+2016-08-24 09:46:26,389 DEBUG: View 2 : 0.430379746835
+2016-08-24 09:46:26,397 DEBUG: View 3 : 0.632911392405
+2016-08-24 09:46:26,539 DEBUG: Best view : Clinic_
+2016-08-24 09:46:29,075 DEBUG: Start: Iteration 43
+2016-08-24 09:46:29,091 DEBUG: View 0 : 0.398734177215
+2016-08-24 09:46:29,099 DEBUG: View 1 : 0.5
+2016-08-24 09:46:29,136 DEBUG: View 2 : 0.651898734177
+2016-08-24 09:46:29,143 DEBUG: View 3 : 0.424050632911
+2016-08-24 09:46:29,287 DEBUG: Best view : RANSeq_
+2016-08-24 09:46:31,887 DEBUG: Start: Iteration 44
+2016-08-24 09:46:31,904 DEBUG: View 0 : 0.506329113924
+2016-08-24 09:46:31,912 DEBUG: View 1 : 0.594936708861
+2016-08-24 09:46:31,949 DEBUG: View 2 : 0.348101265823
+2016-08-24 09:46:31,956 DEBUG: View 3 : 0.462025316456
+2016-08-24 09:46:32,102 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:34,802 DEBUG: Start: Iteration 45
+2016-08-24 09:46:34,819 DEBUG: View 0 : 0.436708860759
+2016-08-24 09:46:34,826 DEBUG: View 1 : 0.601265822785
+2016-08-24 09:46:34,863 DEBUG: View 2 : 0.575949367089
+2016-08-24 09:46:34,870 DEBUG: View 3 : 0.537974683544
+2016-08-24 09:46:35,017 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:37,732 DEBUG: Start: Iteration 46
+2016-08-24 09:46:37,748 DEBUG: View 0 : 0.430379746835
+2016-08-24 09:46:37,756 DEBUG: View 1 : 0.651898734177
+2016-08-24 09:46:37,792 DEBUG: View 2 : 0.398734177215
+2016-08-24 09:46:37,800 DEBUG: View 3 : 0.594936708861
+2016-08-24 09:46:37,949 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:40,720 DEBUG: Start: Iteration 47
+2016-08-24 09:46:40,737 DEBUG: View 0 : 0.537974683544
+2016-08-24 09:46:40,744 DEBUG: View 1 : 0.373417721519
+2016-08-24 09:46:40,781 DEBUG: View 2 : 0.424050632911
+2016-08-24 09:46:40,789 DEBUG: View 3 : 0.506329113924
+2016-08-24 09:46:40,941 DEBUG: Best view : Methyl_
+2016-08-24 09:46:43,774 DEBUG: Start: Iteration 48
+2016-08-24 09:46:43,791 DEBUG: View 0 : 0.455696202532
+2016-08-24 09:46:43,799 DEBUG: View 1 : 0.677215189873
+2016-08-24 09:46:43,835 DEBUG: View 2 : 0.601265822785
+2016-08-24 09:46:43,843 DEBUG: View 3 : 0.443037974684
+2016-08-24 09:46:43,997 DEBUG: Best view : MiRNA__
+2016-08-24 09:46:46,889 DEBUG: Start: Iteration 49
+2016-08-24 09:46:46,906 DEBUG: View 0 : 0.443037974684
+2016-08-24 09:46:46,913 DEBUG: View 1 : 0.29746835443
+2016-08-24 09:46:46,950 DEBUG: View 2 : 0.582278481013
+2016-08-24 09:46:46,958 DEBUG: View 3 : 0.613924050633
+2016-08-24 09:46:47,114 DEBUG: Best view : Clinic_
+2016-08-24 09:46:50,150 DEBUG: Start: Iteration 50
+2016-08-24 09:46:50,167 DEBUG: View 0 : 0.436708860759
+2016-08-24 09:46:50,175 DEBUG: View 1 : 0.537974683544
+2016-08-24 09:46:50,211 DEBUG: View 2 : 0.569620253165
+2016-08-24 09:46:50,219 DEBUG: View 3 : 0.405063291139
+2016-08-24 09:46:50,378 DEBUG: Best view : RANSeq_
+2016-08-24 09:46:53,398 DEBUG: Start: Iteration 51
+2016-08-24 09:46:53,415 DEBUG: View 0 : 0.569620253165
+2016-08-24 09:46:53,423 DEBUG: View 1 : 0.417721518987
+2016-08-24 09:46:53,459 DEBUG: View 2 : 0.386075949367
+2016-08-24 09:46:53,467 DEBUG: View 3 : 0.563291139241
+2016-08-24 09:46:53,629 DEBUG: Best view : Methyl_
+2016-08-24 09:46:56,894 DEBUG: Start: Iteration 52
+2016-08-24 09:46:56,913 DEBUG: View 0 : 0.53164556962
+2016-08-24 09:46:56,921 DEBUG: View 1 : 0.405063291139
+2016-08-24 09:46:56,958 DEBUG: View 2 : 0.443037974684
+2016-08-24 09:46:56,966 DEBUG: View 3 : 0.405063291139
+2016-08-24 09:46:57,131 DEBUG: Best view : Methyl_
+2016-08-24 09:47:00,275 INFO: Start: Classification
+2016-08-24 09:47:07,807 INFO: Done: Fold number 1
+2016-08-24 09:47:07,807 INFO: Start: Fold number 2
+2016-08-24 09:47:09,379 DEBUG: Start: Iteration 1
+2016-08-24 09:47:09,398 DEBUG: View 0 : 0.446540880503
+2016-08-24 09:47:09,405 DEBUG: View 1 : 0.377358490566
+2016-08-24 09:47:09,433 DEBUG: View 2 : 0.622641509434
+2016-08-24 09:47:09,441 DEBUG: View 3 : 0.622641509434
+2016-08-24 09:47:09,482 DEBUG: Best view : RANSeq_
+2016-08-24 09:47:09,568 DEBUG: Start: Iteration 2
+2016-08-24 09:47:09,585 DEBUG: View 0 : 0.459119496855
+2016-08-24 09:47:09,593 DEBUG: View 1 : 0.477987421384
+2016-08-24 09:47:09,630 DEBUG: View 2 : 0.572327044025
+2016-08-24 09:47:09,637 DEBUG: View 3 : 0.389937106918
+2016-08-24 09:47:09,682 DEBUG: Best view : RANSeq_
+2016-08-24 09:47:09,840 DEBUG: Start: Iteration 3
+2016-08-24 09:47:09,856 DEBUG: View 0 : 0.534591194969
+2016-08-24 09:47:09,864 DEBUG: View 1 : 0.610062893082
+2016-08-24 09:47:09,900 DEBUG: View 2 : 0.383647798742
+2016-08-24 09:47:09,908 DEBUG: View 3 : 0.452830188679
+2016-08-24 09:47:09,960 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:10,177 DEBUG: Start: Iteration 4
+2016-08-24 09:47:10,194 DEBUG: View 0 : 0.566037735849
+2016-08-24 09:47:10,201 DEBUG: View 1 : 0.427672955975
+2016-08-24 09:47:10,239 DEBUG: View 2 : 0.408805031447
+2016-08-24 09:47:10,246 DEBUG: View 3 : 0.660377358491
+2016-08-24 09:47:10,301 DEBUG: Best view : Clinic_
+2016-08-24 09:47:10,577 DEBUG: Start: Iteration 5
+2016-08-24 09:47:10,594 DEBUG: View 0 : 0.509433962264
+2016-08-24 09:47:10,601 DEBUG: View 1 : 0.660377358491
+2016-08-24 09:47:10,638 DEBUG: View 2 : 0.490566037736
+2016-08-24 09:47:10,646 DEBUG: View 3 : 0.553459119497
+2016-08-24 09:47:10,703 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:11,037 DEBUG: Start: Iteration 6
+2016-08-24 09:47:11,053 DEBUG: View 0 : 0.660377358491
+2016-08-24 09:47:11,061 DEBUG: View 1 : 0.396226415094
+2016-08-24 09:47:11,098 DEBUG: View 2 : 0.553459119497
+2016-08-24 09:47:11,106 DEBUG: View 3 : 0.540880503145
+2016-08-24 09:47:11,167 DEBUG: Best view : Methyl_
+2016-08-24 09:47:11,562 DEBUG: Start: Iteration 7
+2016-08-24 09:47:11,578 DEBUG: View 0 : 0.339622641509
+2016-08-24 09:47:11,586 DEBUG: View 1 : 0.62893081761
+2016-08-24 09:47:11,623 DEBUG: View 2 : 0.566037735849
+2016-08-24 09:47:11,630 DEBUG: View 3 : 0.465408805031
+2016-08-24 09:47:11,692 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:12,144 DEBUG: Start: Iteration 8
+2016-08-24 09:47:12,160 DEBUG: View 0 : 0.471698113208
+2016-08-24 09:47:12,168 DEBUG: View 1 : 0.654088050314
+2016-08-24 09:47:12,205 DEBUG: View 2 : 0.383647798742
+2016-08-24 09:47:12,212 DEBUG: View 3 : 0.59748427673
+2016-08-24 09:47:12,276 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:12,787 DEBUG: Start: Iteration 9
+2016-08-24 09:47:12,803 DEBUG: View 0 : 0.622641509434
+2016-08-24 09:47:12,811 DEBUG: View 1 : 0.383647798742
+2016-08-24 09:47:12,848 DEBUG: View 2 : 0.389937106918
+2016-08-24 09:47:12,856 DEBUG: View 3 : 0.584905660377
+2016-08-24 09:47:12,923 DEBUG: Best view : Methyl_
+2016-08-24 09:47:13,494 DEBUG: Start: Iteration 10
+2016-08-24 09:47:13,511 DEBUG: View 0 : 0.433962264151
+2016-08-24 09:47:13,519 DEBUG: View 1 : 0.685534591195
+2016-08-24 09:47:13,556 DEBUG: View 2 : 0.452830188679
+2016-08-24 09:47:13,563 DEBUG: View 3 : 0.40251572327
+2016-08-24 09:47:13,632 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:14,261 DEBUG: Start: Iteration 11
+2016-08-24 09:47:14,278 DEBUG: View 0 : 0.584905660377
+2016-08-24 09:47:14,286 DEBUG: View 1 : 0.566037735849
+2016-08-24 09:47:14,322 DEBUG: View 2 : 0.477987421384
+2016-08-24 09:47:14,330 DEBUG: View 3 : 0.440251572327
+2016-08-24 09:47:14,401 DEBUG: Best view : Methyl_
+2016-08-24 09:47:15,092 DEBUG: Start: Iteration 12
+2016-08-24 09:47:15,109 DEBUG: View 0 : 0.301886792453
+2016-08-24 09:47:15,116 DEBUG: View 1 : 0.37106918239
+2016-08-24 09:47:15,153 DEBUG: View 2 : 0.59748427673
+2016-08-24 09:47:15,160 DEBUG: View 3 : 0.528301886792
+2016-08-24 09:47:15,233 DEBUG: Best view : RANSeq_
+2016-08-24 09:47:16,016 DEBUG: Start: Iteration 13
+2016-08-24 09:47:16,033 DEBUG: View 0 : 0.427672955975
+2016-08-24 09:47:16,040 DEBUG: View 1 : 0.660377358491
+2016-08-24 09:47:16,077 DEBUG: View 2 : 0.377358490566
+2016-08-24 09:47:16,084 DEBUG: View 3 : 0.452830188679
+2016-08-24 09:47:16,162 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:17,170 DEBUG: Start: Iteration 14
+2016-08-24 09:47:17,190 DEBUG: View 0 : 0.622641509434
+2016-08-24 09:47:17,199 DEBUG: View 1 : 0.641509433962
+2016-08-24 09:47:17,242 DEBUG: View 2 : 0.584905660377
+2016-08-24 09:47:17,251 DEBUG: View 3 : 0.528301886792
+2016-08-24 09:47:17,335 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:18,276 DEBUG: Start: Iteration 15
+2016-08-24 09:47:18,294 DEBUG: View 0 : 0.440251572327
+2016-08-24 09:47:18,302 DEBUG: View 1 : 0.283018867925
+2016-08-24 09:47:18,343 DEBUG: View 2 : 0.377358490566
+2016-08-24 09:47:18,351 DEBUG: View 3 : 0.522012578616
+2016-08-24 09:47:18,437 DEBUG: Best view : Clinic_
+2016-08-24 09:47:19,473 DEBUG: Start: Iteration 16
+2016-08-24 09:47:19,491 DEBUG: View 0 : 0.509433962264
+2016-08-24 09:47:19,499 DEBUG: View 1 : 0.522012578616
+2016-08-24 09:47:19,535 DEBUG: View 2 : 0.452830188679
+2016-08-24 09:47:19,543 DEBUG: View 3 : 0.40251572327
+2016-08-24 09:47:19,626 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:20,644 DEBUG: Start: Iteration 17
+2016-08-24 09:47:20,661 DEBUG: View 0 : 0.415094339623
+2016-08-24 09:47:20,669 DEBUG: View 1 : 0.452830188679
+2016-08-24 09:47:20,707 DEBUG: View 2 : 0.471698113208
+2016-08-24 09:47:20,714 DEBUG: View 3 : 0.48427672956
+2016-08-24 09:47:20,715 WARNING: WARNING: All bad for iteration 16
+2016-08-24 09:47:20,803 DEBUG: Best view : Clinic_
+2016-08-24 09:47:21,871 DEBUG: Start: Iteration 18
+2016-08-24 09:47:21,889 DEBUG: View 0 : 0.396226415094
+2016-08-24 09:47:21,897 DEBUG: View 1 : 0.62893081761
+2016-08-24 09:47:21,935 DEBUG: View 2 : 0.553459119497
+2016-08-24 09:47:21,942 DEBUG: View 3 : 0.534591194969
+2016-08-24 09:47:22,033 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:23,205 DEBUG: Start: Iteration 19
+2016-08-24 09:47:23,222 DEBUG: View 0 : 0.415094339623
+2016-08-24 09:47:23,230 DEBUG: View 1 : 0.710691823899
+2016-08-24 09:47:23,268 DEBUG: View 2 : 0.660377358491
+2016-08-24 09:47:23,276 DEBUG: View 3 : 0.534591194969
+2016-08-24 09:47:23,370 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:24,573 DEBUG: Start: Iteration 20
+2016-08-24 09:47:24,590 DEBUG: View 0 : 0.459119496855
+2016-08-24 09:47:24,598 DEBUG: View 1 : 0.616352201258
+2016-08-24 09:47:24,636 DEBUG: View 2 : 0.465408805031
+2016-08-24 09:47:24,643 DEBUG: View 3 : 0.415094339623
+2016-08-24 09:47:24,737 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:25,998 DEBUG: Start: Iteration 21
+2016-08-24 09:47:26,016 DEBUG: View 0 : 0.48427672956
+2016-08-24 09:47:26,024 DEBUG: View 1 : 0.616352201258
+2016-08-24 09:47:26,063 DEBUG: View 2 : 0.415094339623
+2016-08-24 09:47:26,071 DEBUG: View 3 : 0.553459119497
+2016-08-24 09:47:26,172 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:27,510 DEBUG: Start: Iteration 22
+2016-08-24 09:47:27,527 DEBUG: View 0 : 0.547169811321
+2016-08-24 09:47:27,534 DEBUG: View 1 : 0.584905660377
+2016-08-24 09:47:27,571 DEBUG: View 2 : 0.540880503145
+2016-08-24 09:47:27,579 DEBUG: View 3 : 0.440251572327
+2016-08-24 09:47:27,682 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:29,064 DEBUG: Start: Iteration 23
+2016-08-24 09:47:29,081 DEBUG: View 0 : 0.534591194969
+2016-08-24 09:47:29,088 DEBUG: View 1 : 0.704402515723
+2016-08-24 09:47:29,125 DEBUG: View 2 : 0.48427672956
+2016-08-24 09:47:29,132 DEBUG: View 3 : 0.471698113208
+2016-08-24 09:47:29,232 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:30,679 DEBUG: Start: Iteration 24
+2016-08-24 09:47:30,696 DEBUG: View 0 : 0.679245283019
+2016-08-24 09:47:30,704 DEBUG: View 1 : 0.691823899371
+2016-08-24 09:47:30,742 DEBUG: View 2 : 0.559748427673
+2016-08-24 09:47:30,750 DEBUG: View 3 : 0.471698113208
+2016-08-24 09:47:30,856 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:32,537 DEBUG: Start: Iteration 25
+2016-08-24 09:47:32,554 DEBUG: View 0 : 0.465408805031
+2016-08-24 09:47:32,562 DEBUG: View 1 : 0.452830188679
+2016-08-24 09:47:32,599 DEBUG: View 2 : 0.40251572327
+2016-08-24 09:47:32,606 DEBUG: View 3 : 0.540880503145
+2016-08-24 09:47:32,710 DEBUG: Best view : Clinic_
+2016-08-24 09:47:34,272 DEBUG: Start: Iteration 26
+2016-08-24 09:47:34,292 DEBUG: View 0 : 0.446540880503
+2016-08-24 09:47:34,303 DEBUG: View 1 : 0.389937106918
+2016-08-24 09:47:34,343 DEBUG: View 2 : 0.509433962264
+2016-08-24 09:47:34,351 DEBUG: View 3 : 0.553459119497
+2016-08-24 09:47:34,466 DEBUG: Best view : Clinic_
+2016-08-24 09:47:36,204 DEBUG: Start: Iteration 27
+2016-08-24 09:47:36,223 DEBUG: View 0 : 0.522012578616
+2016-08-24 09:47:36,234 DEBUG: View 1 : 0.685534591195
+2016-08-24 09:47:36,278 DEBUG: View 2 : 0.578616352201
+2016-08-24 09:47:36,287 DEBUG: View 3 : 0.496855345912
+2016-08-24 09:47:36,415 DEBUG: Best view : MiRNA__
+2016-08-24 09:47:38,235 DEBUG: Start: Iteration 28
+2016-08-24 09:47:38,252 DEBUG: View 0 : 0.660377358491
+2016-08-24 09:47:38,260 DEBUG: View 1 : 0.679245283019
+2016-08-24 09:47:38,297 DEBUG: View 2 : 0.559748427673
+2016-08-24 09:47:38,305 DEBUG: View 3 : 0.641509433962
+2016-08-24 09:47:38,415 DEBUG: Best view : MiRNA__
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-094740-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-094740-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..34b92ceb01d8dbb452625738f7b5ad3c1007f8c8
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-094740-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,15348 @@
+2016-08-24 09:47:40,713 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 09:47:40,714 INFO: Info: Labels used: No, Yes
+2016-08-24 09:47:40,714 INFO: Info: Length of dataset:347
+2016-08-24 09:47:40,716 INFO: ### Main Programm for Multiview Classification
+2016-08-24 09:47:40,716 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 09:47:40,716 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 09:47:40,717 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 09:47:40,717 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 09:47:40,718 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 09:47:40,718 INFO: Done: Read Database Files
+2016-08-24 09:47:40,718 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 09:47:40,721 INFO: Done: Determine validation split
+2016-08-24 09:47:40,721 INFO: Start: Determine 2 folds
+2016-08-24 09:47:40,733 INFO: Info: Length of Learning Sets: 122
+2016-08-24 09:47:40,733 INFO: Info: Length of Testing Sets: 122
+2016-08-24 09:47:40,733 INFO: Info: Length of Validation Set: 103
+2016-08-24 09:47:40,733 INFO: Done: Determine folds
+2016-08-24 09:47:40,733 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 09:47:40,733 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 09:47:40,733 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 09:47:48,128 DEBUG: 0.589798270893Poulet
+2016-08-24 09:47:48,128 DEBUG: 0.521498559078Poulet
+2016-08-24 09:47:48,128 DEBUG: 0.521556195965Poulet
+2016-08-24 09:47:48,128 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:47:48,129 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 09:47:50,083 DEBUG: 0.585360230548Poulet
+2016-08-24 09:47:50,083 DEBUG: 0.573025936599Poulet
+2016-08-24 09:47:50,083 DEBUG: 0.55613832853Poulet
+2016-08-24 09:47:50,083 DEBUG: 0.54507204611Poulet
+2016-08-24 09:47:50,083 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:47:50,084 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 09:48:06,845 DEBUG: 0.559365994236Poulet
+2016-08-24 09:48:06,845 DEBUG: 0.530201729107Poulet
+2016-08-24 09:48:06,846 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:48:06,847 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 09:48:08,580 DEBUG: 0.584034582133Poulet
+2016-08-24 09:48:08,580 DEBUG: 0.556945244957Poulet
+2016-08-24 09:48:08,581 DEBUG: 0.508876080692Poulet
+2016-08-24 09:48:08,581 DEBUG: 0.523170028818Poulet
+2016-08-24 09:48:08,581 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:48:08,581 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 09:49:01,049 DEBUG: 0.563976945245Poulet
+2016-08-24 09:49:01,050 DEBUG: 0.553371757925Poulet
+2016-08-24 09:49:01,050 DEBUG: 0.501268011527Poulet
+2016-08-24 09:49:01,055 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 09:49:01,055 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 09:49:01,055 INFO: Start: Fold number 1
+2016-08-24 09:49:03,043 DEBUG: Start: Iteration 1
+2016-08-24 09:49:03,080 DEBUG: View 0 : 0.601226993865
+2016-08-24 09:49:03,088 DEBUG: View 1 : 0.631901840491
+2016-08-24 09:49:03,116 DEBUG: View 2 : 0.368098159509
+2016-08-24 09:49:03,124 DEBUG: View 3 : 0.368098159509
+2016-08-24 09:49:03,167 DEBUG: Best view : Methyl_
+2016-08-24 09:49:03,245 DEBUG: Start: Iteration 2
+2016-08-24 09:49:03,262 DEBUG: View 0 : 0.558282208589
+2016-08-24 09:49:03,270 DEBUG: View 1 : 0.625766871166
+2016-08-24 09:49:03,307 DEBUG: View 2 : 0.570552147239
+2016-08-24 09:49:03,315 DEBUG: View 3 : 0.466257668712
+2016-08-24 09:49:03,362 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:03,499 DEBUG: Start: Iteration 3
+2016-08-24 09:49:03,516 DEBUG: View 0 : 0.460122699387
+2016-08-24 09:49:03,524 DEBUG: View 1 : 0.680981595092
+2016-08-24 09:49:03,561 DEBUG: View 2 : 0.435582822086
+2016-08-24 09:49:03,569 DEBUG: View 3 : 0.625766871166
+2016-08-24 09:49:03,624 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:03,821 DEBUG: Start: Iteration 4
+2016-08-24 09:49:03,838 DEBUG: View 0 : 0.503067484663
+2016-08-24 09:49:03,846 DEBUG: View 1 : 0.546012269939
+2016-08-24 09:49:03,883 DEBUG: View 2 : 0.429447852761
+2016-08-24 09:49:03,890 DEBUG: View 3 : 0.533742331288
+2016-08-24 09:49:03,947 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:04,204 DEBUG: Start: Iteration 5
+2016-08-24 09:49:04,221 DEBUG: View 0 : 0.662576687117
+2016-08-24 09:49:04,228 DEBUG: View 1 : 0.674846625767
+2016-08-24 09:49:04,266 DEBUG: View 2 : 0.466257668712
+2016-08-24 09:49:04,273 DEBUG: View 3 : 0.429447852761
+2016-08-24 09:49:04,332 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:04,648 DEBUG: Start: Iteration 6
+2016-08-24 09:49:04,665 DEBUG: View 0 : 0.398773006135
+2016-08-24 09:49:04,673 DEBUG: View 1 : 0.527607361963
+2016-08-24 09:49:04,710 DEBUG: View 2 : 0.552147239264
+2016-08-24 09:49:04,717 DEBUG: View 3 : 0.625766871166
+2016-08-24 09:49:04,779 DEBUG: Best view : Clinic_
+2016-08-24 09:49:05,154 DEBUG: Start: Iteration 7
+2016-08-24 09:49:05,170 DEBUG: View 0 : 0.680981595092
+2016-08-24 09:49:05,178 DEBUG: View 1 : 0.478527607362
+2016-08-24 09:49:05,215 DEBUG: View 2 : 0.478527607362
+2016-08-24 09:49:05,223 DEBUG: View 3 : 0.429447852761
+2016-08-24 09:49:05,287 DEBUG: Best view : Methyl_
+2016-08-24 09:49:05,725 DEBUG: Start: Iteration 8
+2016-08-24 09:49:05,741 DEBUG: View 0 : 0.527607361963
+2016-08-24 09:49:05,749 DEBUG: View 1 : 0.429447852761
+2016-08-24 09:49:05,787 DEBUG: View 2 : 0.539877300613
+2016-08-24 09:49:05,795 DEBUG: View 3 : 0.472392638037
+2016-08-24 09:49:05,861 DEBUG: Best view : Methyl_
+2016-08-24 09:49:06,363 DEBUG: Start: Iteration 9
+2016-08-24 09:49:06,380 DEBUG: View 0 : 0.460122699387
+2016-08-24 09:49:06,388 DEBUG: View 1 : 0.546012269939
+2016-08-24 09:49:06,425 DEBUG: View 2 : 0.490797546012
+2016-08-24 09:49:06,433 DEBUG: View 3 : 0.398773006135
+2016-08-24 09:49:06,501 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:07,061 DEBUG: Start: Iteration 10
+2016-08-24 09:49:07,077 DEBUG: View 0 : 0.558282208589
+2016-08-24 09:49:07,085 DEBUG: View 1 : 0.60736196319
+2016-08-24 09:49:07,123 DEBUG: View 2 : 0.41717791411
+2016-08-24 09:49:07,130 DEBUG: View 3 : 0.411042944785
+2016-08-24 09:49:07,201 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:07,822 DEBUG: Start: Iteration 11
+2016-08-24 09:49:07,838 DEBUG: View 0 : 0.638036809816
+2016-08-24 09:49:07,846 DEBUG: View 1 : 0.40490797546
+2016-08-24 09:49:07,884 DEBUG: View 2 : 0.60736196319
+2016-08-24 09:49:07,891 DEBUG: View 3 : 0.429447852761
+2016-08-24 09:49:07,965 DEBUG: Best view : Methyl_
+2016-08-24 09:49:08,649 DEBUG: Start: Iteration 12
+2016-08-24 09:49:08,665 DEBUG: View 0 : 0.564417177914
+2016-08-24 09:49:08,673 DEBUG: View 1 : 0.429447852761
+2016-08-24 09:49:08,710 DEBUG: View 2 : 0.570552147239
+2016-08-24 09:49:08,718 DEBUG: View 3 : 0.601226993865
+2016-08-24 09:49:08,794 DEBUG: Best view : Methyl_
+2016-08-24 09:49:09,540 DEBUG: Start: Iteration 13
+2016-08-24 09:49:09,557 DEBUG: View 0 : 0.576687116564
+2016-08-24 09:49:09,565 DEBUG: View 1 : 0.625766871166
+2016-08-24 09:49:09,604 DEBUG: View 2 : 0.484662576687
+2016-08-24 09:49:09,612 DEBUG: View 3 : 0.552147239264
+2016-08-24 09:49:09,691 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:10,498 DEBUG: Start: Iteration 14
+2016-08-24 09:49:10,515 DEBUG: View 0 : 0.39263803681
+2016-08-24 09:49:10,522 DEBUG: View 1 : 0.60736196319
+2016-08-24 09:49:10,562 DEBUG: View 2 : 0.40490797546
+2016-08-24 09:49:10,570 DEBUG: View 3 : 0.552147239264
+2016-08-24 09:49:10,650 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:11,517 DEBUG: Start: Iteration 15
+2016-08-24 09:49:11,534 DEBUG: View 0 : 0.59509202454
+2016-08-24 09:49:11,541 DEBUG: View 1 : 0.288343558282
+2016-08-24 09:49:11,581 DEBUG: View 2 : 0.576687116564
+2016-08-24 09:49:11,589 DEBUG: View 3 : 0.41717791411
+2016-08-24 09:49:11,672 DEBUG: Best view : Methyl_
+2016-08-24 09:49:12,603 DEBUG: Start: Iteration 16
+2016-08-24 09:49:12,619 DEBUG: View 0 : 0.38036809816
+2016-08-24 09:49:12,627 DEBUG: View 1 : 0.58282208589
+2016-08-24 09:49:12,667 DEBUG: View 2 : 0.515337423313
+2016-08-24 09:49:12,675 DEBUG: View 3 : 0.466257668712
+2016-08-24 09:49:12,760 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:13,748 DEBUG: Start: Iteration 17
+2016-08-24 09:49:13,764 DEBUG: View 0 : 0.441717791411
+2016-08-24 09:49:13,772 DEBUG: View 1 : 0.374233128834
+2016-08-24 09:49:13,812 DEBUG: View 2 : 0.478527607362
+2016-08-24 09:49:13,820 DEBUG: View 3 : 0.546012269939
+2016-08-24 09:49:13,907 DEBUG: Best view : Clinic_
+2016-08-24 09:49:14,953 DEBUG: Start: Iteration 18
+2016-08-24 09:49:14,970 DEBUG: View 0 : 0.650306748466
+2016-08-24 09:49:14,978 DEBUG: View 1 : 0.269938650307
+2016-08-24 09:49:15,018 DEBUG: View 2 : 0.644171779141
+2016-08-24 09:49:15,026 DEBUG: View 3 : 0.398773006135
+2016-08-24 09:49:15,115 DEBUG: Best view : Methyl_
+2016-08-24 09:49:16,227 DEBUG: Start: Iteration 19
+2016-08-24 09:49:16,244 DEBUG: View 0 : 0.662576687117
+2016-08-24 09:49:16,252 DEBUG: View 1 : 0.398773006135
+2016-08-24 09:49:16,291 DEBUG: View 2 : 0.411042944785
+2016-08-24 09:49:16,299 DEBUG: View 3 : 0.613496932515
+2016-08-24 09:49:16,391 DEBUG: Best view : Methyl_
+2016-08-24 09:49:17,580 DEBUG: Start: Iteration 20
+2016-08-24 09:49:17,597 DEBUG: View 0 : 0.588957055215
+2016-08-24 09:49:17,605 DEBUG: View 1 : 0.429447852761
+2016-08-24 09:49:17,645 DEBUG: View 2 : 0.601226993865
+2016-08-24 09:49:17,653 DEBUG: View 3 : 0.39263803681
+2016-08-24 09:49:17,747 DEBUG: Best view : Methyl_
+2016-08-24 09:49:18,983 DEBUG: Start: Iteration 21
+2016-08-24 09:49:19,000 DEBUG: View 0 : 0.41717791411
+2016-08-24 09:49:19,008 DEBUG: View 1 : 0.515337423313
+2016-08-24 09:49:19,048 DEBUG: View 2 : 0.515337423313
+2016-08-24 09:49:19,056 DEBUG: View 3 : 0.40490797546
+2016-08-24 09:49:19,152 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:20,448 DEBUG: Start: Iteration 22
+2016-08-24 09:49:20,464 DEBUG: View 0 : 0.39263803681
+2016-08-24 09:49:20,472 DEBUG: View 1 : 0.730061349693
+2016-08-24 09:49:20,511 DEBUG: View 2 : 0.558282208589
+2016-08-24 09:49:20,520 DEBUG: View 3 : 0.650306748466
+2016-08-24 09:49:20,619 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:21,975 DEBUG: Start: Iteration 23
+2016-08-24 09:49:21,992 DEBUG: View 0 : 0.527607361963
+2016-08-24 09:49:22,000 DEBUG: View 1 : 0.576687116564
+2016-08-24 09:49:22,039 DEBUG: View 2 : 0.631901840491
+2016-08-24 09:49:22,047 DEBUG: View 3 : 0.503067484663
+2016-08-24 09:49:22,149 DEBUG: Best view : RANSeq_
+2016-08-24 09:49:23,580 DEBUG: Start: Iteration 24
+2016-08-24 09:49:23,596 DEBUG: View 0 : 0.58282208589
+2016-08-24 09:49:23,604 DEBUG: View 1 : 0.533742331288
+2016-08-24 09:49:23,644 DEBUG: View 2 : 0.576687116564
+2016-08-24 09:49:23,653 DEBUG: View 3 : 0.447852760736
+2016-08-24 09:49:23,756 DEBUG: Best view : RANSeq_
+2016-08-24 09:49:25,260 DEBUG: Start: Iteration 25
+2016-08-24 09:49:25,277 DEBUG: View 0 : 0.58282208589
+2016-08-24 09:49:25,285 DEBUG: View 1 : 0.60736196319
+2016-08-24 09:49:25,324 DEBUG: View 2 : 0.423312883436
+2016-08-24 09:49:25,333 DEBUG: View 3 : 0.60736196319
+2016-08-24 09:49:25,439 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:26,999 DEBUG: Start: Iteration 26
+2016-08-24 09:49:27,016 DEBUG: View 0 : 0.588957055215
+2016-08-24 09:49:27,024 DEBUG: View 1 : 0.539877300613
+2016-08-24 09:49:27,063 DEBUG: View 2 : 0.546012269939
+2016-08-24 09:49:27,071 DEBUG: View 3 : 0.625766871166
+2016-08-24 09:49:27,179 DEBUG: Best view : Clinic_
+2016-08-24 09:49:28,797 DEBUG: Start: Iteration 27
+2016-08-24 09:49:28,814 DEBUG: View 0 : 0.552147239264
+2016-08-24 09:49:28,822 DEBUG: View 1 : 0.674846625767
+2016-08-24 09:49:28,862 DEBUG: View 2 : 0.662576687117
+2016-08-24 09:49:28,870 DEBUG: View 3 : 0.496932515337
+2016-08-24 09:49:28,980 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:30,657 DEBUG: Start: Iteration 28
+2016-08-24 09:49:30,674 DEBUG: View 0 : 0.472392638037
+2016-08-24 09:49:30,681 DEBUG: View 1 : 0.674846625767
+2016-08-24 09:49:30,721 DEBUG: View 2 : 0.588957055215
+2016-08-24 09:49:30,729 DEBUG: View 3 : 0.564417177914
+2016-08-24 09:49:30,841 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:32,609 DEBUG: Start: Iteration 29
+2016-08-24 09:49:32,625 DEBUG: View 0 : 0.717791411043
+2016-08-24 09:49:32,633 DEBUG: View 1 : 0.650306748466
+2016-08-24 09:49:32,673 DEBUG: View 2 : 0.546012269939
+2016-08-24 09:49:32,681 DEBUG: View 3 : 0.411042944785
+2016-08-24 09:49:32,796 DEBUG: Best view : Methyl_
+2016-08-24 09:49:34,618 DEBUG: Start: Iteration 30
+2016-08-24 09:49:34,635 DEBUG: View 0 : 0.41717791411
+2016-08-24 09:49:34,643 DEBUG: View 1 : 0.355828220859
+2016-08-24 09:49:34,684 DEBUG: View 2 : 0.521472392638
+2016-08-24 09:49:34,692 DEBUG: View 3 : 0.509202453988
+2016-08-24 09:49:34,811 DEBUG: Best view : RANSeq_
+2016-08-24 09:49:36,776 DEBUG: Start: Iteration 31
+2016-08-24 09:49:36,793 DEBUG: View 0 : 0.539877300613
+2016-08-24 09:49:36,801 DEBUG: View 1 : 0.386503067485
+2016-08-24 09:49:36,841 DEBUG: View 2 : 0.374233128834
+2016-08-24 09:49:36,850 DEBUG: View 3 : 0.533742331288
+2016-08-24 09:49:36,978 DEBUG: Best view : Methyl_
+2016-08-24 09:49:38,949 DEBUG: Start: Iteration 32
+2016-08-24 09:49:38,966 DEBUG: View 0 : 0.423312883436
+2016-08-24 09:49:38,974 DEBUG: View 1 : 0.478527607362
+2016-08-24 09:49:39,014 DEBUG: View 2 : 0.466257668712
+2016-08-24 09:49:39,022 DEBUG: View 3 : 0.631901840491
+2016-08-24 09:49:39,143 DEBUG: Best view : Clinic_
+2016-08-24 09:49:41,144 DEBUG: Start: Iteration 33
+2016-08-24 09:49:41,161 DEBUG: View 0 : 0.515337423313
+2016-08-24 09:49:41,169 DEBUG: View 1 : 0.509202453988
+2016-08-24 09:49:41,208 DEBUG: View 2 : 0.447852760736
+2016-08-24 09:49:41,217 DEBUG: View 3 : 0.460122699387
+2016-08-24 09:49:41,341 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:43,399 DEBUG: Start: Iteration 34
+2016-08-24 09:49:43,415 DEBUG: View 0 : 0.601226993865
+2016-08-24 09:49:43,423 DEBUG: View 1 : 0.613496932515
+2016-08-24 09:49:43,463 DEBUG: View 2 : 0.435582822086
+2016-08-24 09:49:43,471 DEBUG: View 3 : 0.39263803681
+2016-08-24 09:49:43,596 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:45,710 DEBUG: Start: Iteration 35
+2016-08-24 09:49:45,726 DEBUG: View 0 : 0.521472392638
+2016-08-24 09:49:45,734 DEBUG: View 1 : 0.503067484663
+2016-08-24 09:49:45,774 DEBUG: View 2 : 0.386503067485
+2016-08-24 09:49:45,782 DEBUG: View 3 : 0.411042944785
+2016-08-24 09:49:45,910 DEBUG: Best view : Methyl_
+2016-08-24 09:49:48,090 DEBUG: Start: Iteration 36
+2016-08-24 09:49:48,107 DEBUG: View 0 : 0.539877300613
+2016-08-24 09:49:48,115 DEBUG: View 1 : 0.478527607362
+2016-08-24 09:49:48,155 DEBUG: View 2 : 0.576687116564
+2016-08-24 09:49:48,163 DEBUG: View 3 : 0.539877300613
+2016-08-24 09:49:48,293 DEBUG: Best view : RANSeq_
+2016-08-24 09:49:50,546 DEBUG: Start: Iteration 37
+2016-08-24 09:49:50,562 DEBUG: View 0 : 0.447852760736
+2016-08-24 09:49:50,570 DEBUG: View 1 : 0.705521472393
+2016-08-24 09:49:50,610 DEBUG: View 2 : 0.509202453988
+2016-08-24 09:49:50,618 DEBUG: View 3 : 0.570552147239
+2016-08-24 09:49:50,750 DEBUG: Best view : MiRNA__
+2016-08-24 09:49:53,060 DEBUG: Start: Iteration 38
+2016-08-24 09:49:53,077 DEBUG: View 0 : 0.509202453988
+2016-08-24 09:49:53,085 DEBUG: View 1 : 0.558282208589
+2016-08-24 09:49:53,124 DEBUG: View 2 : 0.423312883436
+2016-08-24 09:49:53,133 DEBUG: View 3 : 0.61963190184
+2016-08-24 09:49:53,267 DEBUG: Best view : Clinic_
+2016-08-24 09:49:55,637 DEBUG: Start: Iteration 39
+2016-08-24 09:49:55,653 DEBUG: View 0 : 0.337423312883
+2016-08-24 09:49:55,661 DEBUG: View 1 : 0.38036809816
+2016-08-24 09:49:55,701 DEBUG: View 2 : 0.423312883436
+2016-08-24 09:49:55,709 DEBUG: View 3 : 0.601226993865
+2016-08-24 09:49:55,846 DEBUG: Best view : Clinic_
+2016-08-24 09:49:58,274 DEBUG: Start: Iteration 40
+2016-08-24 09:49:58,290 DEBUG: View 0 : 0.60736196319
+2016-08-24 09:49:58,298 DEBUG: View 1 : 0.509202453988
+2016-08-24 09:49:58,338 DEBUG: View 2 : 0.631901840491
+2016-08-24 09:49:58,346 DEBUG: View 3 : 0.361963190184
+2016-08-24 09:49:58,485 DEBUG: Best view : Methyl_
+2016-08-24 09:50:00,977 DEBUG: Start: Iteration 41
+2016-08-24 09:50:00,993 DEBUG: View 0 : 0.496932515337
+2016-08-24 09:50:01,001 DEBUG: View 1 : 0.58282208589
+2016-08-24 09:50:01,042 DEBUG: View 2 : 0.411042944785
+2016-08-24 09:50:01,050 DEBUG: View 3 : 0.429447852761
+2016-08-24 09:50:01,192 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:03,745 DEBUG: Start: Iteration 42
+2016-08-24 09:50:03,761 DEBUG: View 0 : 0.521472392638
+2016-08-24 09:50:03,769 DEBUG: View 1 : 0.650306748466
+2016-08-24 09:50:03,810 DEBUG: View 2 : 0.625766871166
+2016-08-24 09:50:03,818 DEBUG: View 3 : 0.539877300613
+2016-08-24 09:50:03,961 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:06,572 DEBUG: Start: Iteration 43
+2016-08-24 09:50:06,589 DEBUG: View 0 : 0.521472392638
+2016-08-24 09:50:06,597 DEBUG: View 1 : 0.423312883436
+2016-08-24 09:50:06,637 DEBUG: View 2 : 0.441717791411
+2016-08-24 09:50:06,646 DEBUG: View 3 : 0.558282208589
+2016-08-24 09:50:06,792 DEBUG: Best view : Methyl_
+2016-08-24 09:50:09,466 DEBUG: Start: Iteration 44
+2016-08-24 09:50:09,483 DEBUG: View 0 : 0.466257668712
+2016-08-24 09:50:09,491 DEBUG: View 1 : 0.472392638037
+2016-08-24 09:50:09,532 DEBUG: View 2 : 0.441717791411
+2016-08-24 09:50:09,541 DEBUG: View 3 : 0.398773006135
+2016-08-24 09:50:09,541 WARNING: WARNING: All bad for iteration 43
+2016-08-24 09:50:09,689 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:12,423 DEBUG: Start: Iteration 45
+2016-08-24 09:50:12,440 DEBUG: View 0 : 0.38036809816
+2016-08-24 09:50:12,447 DEBUG: View 1 : 0.558282208589
+2016-08-24 09:50:12,489 DEBUG: View 2 : 0.411042944785
+2016-08-24 09:50:12,498 DEBUG: View 3 : 0.625766871166
+2016-08-24 09:50:12,649 DEBUG: Best view : Clinic_
+2016-08-24 09:50:15,438 DEBUG: Start: Iteration 46
+2016-08-24 09:50:15,455 DEBUG: View 0 : 0.730061349693
+2016-08-24 09:50:15,463 DEBUG: View 1 : 0.374233128834
+2016-08-24 09:50:15,505 DEBUG: View 2 : 0.576687116564
+2016-08-24 09:50:15,514 DEBUG: View 3 : 0.613496932515
+2016-08-24 09:50:15,667 DEBUG: Best view : Methyl_
+2016-08-24 09:50:18,525 DEBUG: Start: Iteration 47
+2016-08-24 09:50:18,542 DEBUG: View 0 : 0.423312883436
+2016-08-24 09:50:18,549 DEBUG: View 1 : 0.656441717791
+2016-08-24 09:50:18,591 DEBUG: View 2 : 0.429447852761
+2016-08-24 09:50:18,600 DEBUG: View 3 : 0.460122699387
+2016-08-24 09:50:18,756 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:21,672 DEBUG: Start: Iteration 48
+2016-08-24 09:50:21,688 DEBUG: View 0 : 0.355828220859
+2016-08-24 09:50:21,696 DEBUG: View 1 : 0.39263803681
+2016-08-24 09:50:21,740 DEBUG: View 2 : 0.411042944785
+2016-08-24 09:50:21,749 DEBUG: View 3 : 0.435582822086
+2016-08-24 09:50:21,749 WARNING: WARNING: All bad for iteration 47
+2016-08-24 09:50:21,907 DEBUG: Best view : Clinic_
+2016-08-24 09:50:24,889 DEBUG: Start: Iteration 49
+2016-08-24 09:50:24,906 DEBUG: View 0 : 0.521472392638
+2016-08-24 09:50:24,913 DEBUG: View 1 : 0.680981595092
+2016-08-24 09:50:24,957 DEBUG: View 2 : 0.38036809816
+2016-08-24 09:50:24,966 DEBUG: View 3 : 0.558282208589
+2016-08-24 09:50:25,137 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:28,192 DEBUG: Start: Iteration 50
+2016-08-24 09:50:28,209 DEBUG: View 0 : 0.40490797546
+2016-08-24 09:50:28,217 DEBUG: View 1 : 0.650306748466
+2016-08-24 09:50:28,261 DEBUG: View 2 : 0.625766871166
+2016-08-24 09:50:28,270 DEBUG: View 3 : 0.429447852761
+2016-08-24 09:50:28,433 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:31,590 DEBUG: Start: Iteration 51
+2016-08-24 09:50:31,607 DEBUG: View 0 : 0.40490797546
+2016-08-24 09:50:31,615 DEBUG: View 1 : 0.447852760736
+2016-08-24 09:50:31,660 DEBUG: View 2 : 0.490797546012
+2016-08-24 09:50:31,669 DEBUG: View 3 : 0.644171779141
+2016-08-24 09:50:31,836 DEBUG: Best view : Clinic_
+2016-08-24 09:50:35,243 DEBUG: Start: Iteration 52
+2016-08-24 09:50:35,259 DEBUG: View 0 : 0.588957055215
+2016-08-24 09:50:35,267 DEBUG: View 1 : 0.38036809816
+2016-08-24 09:50:35,313 DEBUG: View 2 : 0.509202453988
+2016-08-24 09:50:35,322 DEBUG: View 3 : 0.564417177914
+2016-08-24 09:50:35,492 DEBUG: Best view : Methyl_
+2016-08-24 09:50:38,719 DEBUG: Start: Iteration 53
+2016-08-24 09:50:38,736 DEBUG: View 0 : 0.521472392638
+2016-08-24 09:50:38,744 DEBUG: View 1 : 0.263803680982
+2016-08-24 09:50:38,789 DEBUG: View 2 : 0.453987730061
+2016-08-24 09:50:38,798 DEBUG: View 3 : 0.41717791411
+2016-08-24 09:50:38,970 DEBUG: Best view : Methyl_
+2016-08-24 09:50:42,262 DEBUG: Start: Iteration 54
+2016-08-24 09:50:42,278 DEBUG: View 0 : 0.546012269939
+2016-08-24 09:50:42,286 DEBUG: View 1 : 0.460122699387
+2016-08-24 09:50:42,334 DEBUG: View 2 : 0.539877300613
+2016-08-24 09:50:42,343 DEBUG: View 3 : 0.564417177914
+2016-08-24 09:50:42,517 DEBUG: Best view : Clinic_
+2016-08-24 09:50:45,859 DEBUG: Start: Iteration 55
+2016-08-24 09:50:45,876 DEBUG: View 0 : 0.38036809816
+2016-08-24 09:50:45,884 DEBUG: View 1 : 0.374233128834
+2016-08-24 09:50:45,932 DEBUG: View 2 : 0.484662576687
+2016-08-24 09:50:45,942 DEBUG: View 3 : 0.60736196319
+2016-08-24 09:50:46,117 DEBUG: Best view : Clinic_
+2016-08-24 09:50:49,519 DEBUG: Start: Iteration 56
+2016-08-24 09:50:49,536 DEBUG: View 0 : 0.564417177914
+2016-08-24 09:50:49,543 DEBUG: View 1 : 0.736196319018
+2016-08-24 09:50:49,592 DEBUG: View 2 : 0.515337423313
+2016-08-24 09:50:49,601 DEBUG: View 3 : 0.527607361963
+2016-08-24 09:50:49,778 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:53,243 DEBUG: Start: Iteration 57
+2016-08-24 09:50:53,259 DEBUG: View 0 : 0.668711656442
+2016-08-24 09:50:53,267 DEBUG: View 1 : 0.687116564417
+2016-08-24 09:50:53,315 DEBUG: View 2 : 0.631901840491
+2016-08-24 09:50:53,325 DEBUG: View 3 : 0.576687116564
+2016-08-24 09:50:53,505 DEBUG: Best view : MiRNA__
+2016-08-24 09:50:57,031 DEBUG: Start: Iteration 58
+2016-08-24 09:50:57,047 DEBUG: View 0 : 0.466257668712
+2016-08-24 09:50:57,055 DEBUG: View 1 : 0.650306748466
+2016-08-24 09:50:57,104 DEBUG: View 2 : 0.503067484663
+2016-08-24 09:50:57,113 DEBUG: View 3 : 0.61963190184
+2016-08-24 09:50:57,296 DEBUG: Best view : MiRNA__
+2016-08-24 09:51:00,872 DEBUG: Start: Iteration 59
+2016-08-24 09:51:00,889 DEBUG: View 0 : 0.423312883436
+2016-08-24 09:51:00,897 DEBUG: View 1 : 0.472392638037
+2016-08-24 09:51:00,945 DEBUG: View 2 : 0.453987730061
+2016-08-24 09:51:00,954 DEBUG: View 3 : 0.39263803681
+2016-08-24 09:51:00,954 WARNING: WARNING: All bad for iteration 58
+2016-08-24 09:51:01,138 DEBUG: Best view : RANSeq_
+2016-08-24 09:51:04,914 DEBUG: Start: Iteration 60
+2016-08-24 09:51:04,931 DEBUG: View 0 : 0.570552147239
+2016-08-24 09:51:04,939 DEBUG: View 1 : 0.355828220859
+2016-08-24 09:51:04,987 DEBUG: View 2 : 0.552147239264
+2016-08-24 09:51:04,997 DEBUG: View 3 : 0.570552147239
+2016-08-24 09:51:05,188 DEBUG: Best view : Methyl_
+2016-08-24 09:51:08,910 DEBUG: Start: Iteration 61
+2016-08-24 09:51:08,927 DEBUG: View 0 : 0.58282208589
+2016-08-24 09:51:08,934 DEBUG: View 1 : 0.319018404908
+2016-08-24 09:51:08,981 DEBUG: View 2 : 0.374233128834
+2016-08-24 09:51:08,990 DEBUG: View 3 : 0.558282208589
+2016-08-24 09:51:09,179 DEBUG: Best view : Methyl_
+2016-08-24 09:51:12,965 DEBUG: Start: Iteration 62
+2016-08-24 09:51:12,981 DEBUG: View 0 : 0.570552147239
+2016-08-24 09:51:12,989 DEBUG: View 1 : 0.558282208589
+2016-08-24 09:51:13,036 DEBUG: View 2 : 0.503067484663
+2016-08-24 09:51:13,046 DEBUG: View 3 : 0.539877300613
+2016-08-24 09:51:13,236 DEBUG: Best view : Methyl_
+2016-08-24 09:51:17,077 DEBUG: Start: Iteration 63
+2016-08-24 09:51:17,094 DEBUG: View 0 : 0.441717791411
+2016-08-24 09:51:17,102 DEBUG: View 1 : 0.61963190184
+2016-08-24 09:51:17,150 DEBUG: View 2 : 0.472392638037
+2016-08-24 09:51:17,159 DEBUG: View 3 : 0.447852760736
+2016-08-24 09:51:17,355 DEBUG: Best view : MiRNA__
+2016-08-24 09:51:21,260 DEBUG: Start: Iteration 64
+2016-08-24 09:51:21,276 DEBUG: View 0 : 0.631901840491
+2016-08-24 09:51:21,284 DEBUG: View 1 : 0.631901840491
+2016-08-24 09:51:21,333 DEBUG: View 2 : 0.521472392638
+2016-08-24 09:51:21,342 DEBUG: View 3 : 0.472392638037
+2016-08-24 09:51:21,536 DEBUG: Best view : Methyl_
+2016-08-24 09:51:25,514 DEBUG: Start: Iteration 65
+2016-08-24 09:51:25,531 DEBUG: View 0 : 0.558282208589
+2016-08-24 09:51:25,538 DEBUG: View 1 : 0.472392638037
+2016-08-24 09:51:25,586 DEBUG: View 2 : 0.386503067485
+2016-08-24 09:51:25,595 DEBUG: View 3 : 0.613496932515
+2016-08-24 09:51:25,791 DEBUG: Best view : Clinic_
+2016-08-24 09:51:29,825 DEBUG: Start: Iteration 66
+2016-08-24 09:51:29,842 DEBUG: View 0 : 0.546012269939
+2016-08-24 09:51:29,850 DEBUG: View 1 : 0.466257668712
+2016-08-24 09:51:29,898 DEBUG: View 2 : 0.503067484663
+2016-08-24 09:51:29,907 DEBUG: View 3 : 0.374233128834
+2016-08-24 09:51:30,105 DEBUG: Best view : Methyl_
+2016-08-24 09:51:34,197 DEBUG: Start: Iteration 67
+2016-08-24 09:51:34,214 DEBUG: View 0 : 0.509202453988
+2016-08-24 09:51:34,222 DEBUG: View 1 : 0.625766871166
+2016-08-24 09:51:34,270 DEBUG: View 2 : 0.558282208589
+2016-08-24 09:51:34,279 DEBUG: View 3 : 0.60736196319
+2016-08-24 09:51:34,480 DEBUG: Best view : MiRNA__
+2016-08-24 09:51:38,632 DEBUG: Start: Iteration 68
+2016-08-24 09:51:38,649 DEBUG: View 0 : 0.662576687117
+2016-08-24 09:51:38,657 DEBUG: View 1 : 0.662576687117
+2016-08-24 09:51:38,704 DEBUG: View 2 : 0.478527607362
+2016-08-24 09:51:38,713 DEBUG: View 3 : 0.447852760736
+2016-08-24 09:51:38,916 DEBUG: Best view : Methyl_
+2016-08-24 09:51:43,129 DEBUG: Start: Iteration 69
+2016-08-24 09:51:43,145 DEBUG: View 0 : 0.644171779141
+2016-08-24 09:51:43,153 DEBUG: View 1 : 0.355828220859
+2016-08-24 09:51:43,201 DEBUG: View 2 : 0.386503067485
+2016-08-24 09:51:43,210 DEBUG: View 3 : 0.59509202454
+2016-08-24 09:51:43,415 DEBUG: Best view : Methyl_
+2016-08-24 09:51:47,699 DEBUG: Start: Iteration 70
+2016-08-24 09:51:47,715 DEBUG: View 0 : 0.466257668712
+2016-08-24 09:51:47,723 DEBUG: View 1 : 0.717791411043
+2016-08-24 09:51:47,771 DEBUG: View 2 : 0.411042944785
+2016-08-24 09:51:47,780 DEBUG: View 3 : 0.472392638037
+2016-08-24 09:51:47,988 DEBUG: Best view : MiRNA__
+2016-08-24 09:51:52,330 DEBUG: Start: Iteration 71
+2016-08-24 09:51:52,347 DEBUG: View 0 : 0.411042944785
+2016-08-24 09:51:52,354 DEBUG: View 1 : 0.58282208589
+2016-08-24 09:51:52,402 DEBUG: View 2 : 0.490797546012
+2016-08-24 09:51:52,411 DEBUG: View 3 : 0.552147239264
+2016-08-24 09:51:52,621 DEBUG: Best view : MiRNA__
+2016-08-24 09:51:57,005 DEBUG: Start: Iteration 72
+2016-08-24 09:51:57,022 DEBUG: View 0 : 0.411042944785
+2016-08-24 09:51:57,030 DEBUG: View 1 : 0.705521472393
+2016-08-24 09:51:57,078 DEBUG: View 2 : 0.564417177914
+2016-08-24 09:51:57,087 DEBUG: View 3 : 0.613496932515
+2016-08-24 09:51:57,298 DEBUG: Best view : MiRNA__
+2016-08-24 09:52:01,758 DEBUG: Start: Iteration 73
+2016-08-24 09:52:01,774 DEBUG: View 0 : 0.564417177914
+2016-08-24 09:52:01,782 DEBUG: View 1 : 0.644171779141
+2016-08-24 09:52:01,828 DEBUG: View 2 : 0.533742331288
+2016-08-24 09:52:01,837 DEBUG: View 3 : 0.546012269939
+2016-08-24 09:52:02,052 DEBUG: Best view : MiRNA__
+2016-08-24 09:52:06,564 DEBUG: Start: Iteration 74
+2016-08-24 09:52:06,580 DEBUG: View 0 : 0.39263803681
+2016-08-24 09:52:06,588 DEBUG: View 1 : 0.251533742331
+2016-08-24 09:52:06,637 DEBUG: View 2 : 0.466257668712
+2016-08-24 09:52:06,646 DEBUG: View 3 : 0.601226993865
+2016-08-24 09:52:06,862 DEBUG: Best view : Clinic_
+2016-08-24 09:52:11,562 DEBUG: Start: Iteration 75
+2016-08-24 09:52:11,579 DEBUG: View 0 : 0.58282208589
+2016-08-24 09:52:11,588 DEBUG: View 1 : 0.650306748466
+2016-08-24 09:52:11,636 DEBUG: View 2 : 0.466257668712
+2016-08-24 09:52:11,646 DEBUG: View 3 : 0.564417177914
+2016-08-24 09:52:11,883 DEBUG: Best view : MiRNA__
+2016-08-24 09:52:17,020 DEBUG: Start: Iteration 76
+2016-08-24 09:52:17,038 DEBUG: View 0 : 0.447852760736
+2016-08-24 09:52:17,046 DEBUG: View 1 : 0.374233128834
+2016-08-24 09:52:17,097 DEBUG: View 2 : 0.564417177914
+2016-08-24 09:52:17,105 DEBUG: View 3 : 0.60736196319
+2016-08-24 09:52:17,339 DEBUG: Best view : Clinic_
+2016-08-24 09:52:22,234 DEBUG: Start: Iteration 77
+2016-08-24 09:52:22,251 DEBUG: View 0 : 0.588957055215
+2016-08-24 09:52:22,259 DEBUG: View 1 : 0.558282208589
+2016-08-24 09:52:22,297 DEBUG: View 2 : 0.656441717791
+2016-08-24 09:52:22,305 DEBUG: View 3 : 0.59509202454
+2016-08-24 09:52:22,535 DEBUG: Best view : RANSeq_
+2016-08-24 09:52:27,433 DEBUG: Start: Iteration 78
+2016-08-24 09:52:27,450 DEBUG: View 0 : 0.411042944785
+2016-08-24 09:52:27,458 DEBUG: View 1 : 0.484662576687
+2016-08-24 09:52:27,496 DEBUG: View 2 : 0.466257668712
+2016-08-24 09:52:27,503 DEBUG: View 3 : 0.58282208589
+2016-08-24 09:52:27,729 DEBUG: Best view : Clinic_
+2016-08-24 09:52:32,667 DEBUG: Start: Iteration 79
+2016-08-24 09:52:32,684 DEBUG: View 0 : 0.411042944785
+2016-08-24 09:52:32,692 DEBUG: View 1 : 0.59509202454
+2016-08-24 09:52:32,730 DEBUG: View 2 : 0.61963190184
+2016-08-24 09:52:32,737 DEBUG: View 3 : 0.613496932515
+2016-08-24 09:52:32,967 DEBUG: Best view : RANSeq_
+2016-08-24 09:52:38,035 DEBUG: Start: Iteration 80
+2016-08-24 09:52:38,053 DEBUG: View 0 : 0.503067484663
+2016-08-24 09:52:38,061 DEBUG: View 1 : 0.61963190184
+2016-08-24 09:52:38,101 DEBUG: View 2 : 0.558282208589
+2016-08-24 09:52:38,109 DEBUG: View 3 : 0.576687116564
+2016-08-24 09:52:38,351 DEBUG: Best view : MiRNA__
+2016-08-24 09:52:43,584 DEBUG: Start: Iteration 81
+2016-08-24 09:52:43,601 DEBUG: View 0 : 0.472392638037
+2016-08-24 09:52:43,609 DEBUG: View 1 : 0.509202453988
+2016-08-24 09:52:43,648 DEBUG: View 2 : 0.386503067485
+2016-08-24 09:52:43,656 DEBUG: View 3 : 0.564417177914
+2016-08-24 09:52:43,897 DEBUG: Best view : Clinic_
+2016-08-24 09:52:49,124 DEBUG: Start: Iteration 82
+2016-08-24 09:52:49,141 DEBUG: View 0 : 0.398773006135
+2016-08-24 09:52:49,150 DEBUG: View 1 : 0.625766871166
+2016-08-24 09:52:49,191 DEBUG: View 2 : 0.59509202454
+2016-08-24 09:52:49,199 DEBUG: View 3 : 0.58282208589
+2016-08-24 09:52:49,451 DEBUG: Best view : MiRNA__
+2016-08-24 09:52:54,668 DEBUG: Start: Iteration 83
+2016-08-24 09:52:54,685 DEBUG: View 0 : 0.251533742331
+2016-08-24 09:52:54,693 DEBUG: View 1 : 0.539877300613
+2016-08-24 09:52:54,731 DEBUG: View 2 : 0.429447852761
+2016-08-24 09:52:54,739 DEBUG: View 3 : 0.423312883436
+2016-08-24 09:52:54,986 DEBUG: Best view : MiRNA__
+2016-08-24 09:53:00,332 DEBUG: Start: Iteration 84
+2016-08-24 09:53:00,349 DEBUG: View 0 : 0.411042944785
+2016-08-24 09:53:00,357 DEBUG: View 1 : 0.368098159509
+2016-08-24 09:53:00,394 DEBUG: View 2 : 0.521472392638
+2016-08-24 09:53:00,402 DEBUG: View 3 : 0.576687116564
+2016-08-24 09:53:00,642 DEBUG: Best view : Clinic_
+2016-08-24 09:53:05,890 DEBUG: Start: Iteration 85
+2016-08-24 09:53:05,908 DEBUG: View 0 : 0.343558282209
+2016-08-24 09:53:05,916 DEBUG: View 1 : 0.625766871166
+2016-08-24 09:53:05,955 DEBUG: View 2 : 0.472392638037
+2016-08-24 09:53:05,963 DEBUG: View 3 : 0.564417177914
+2016-08-24 09:53:06,217 DEBUG: Best view : MiRNA__
+2016-08-24 09:53:11,740 DEBUG: Start: Iteration 86
+2016-08-24 09:53:11,758 DEBUG: View 0 : 0.398773006135
+2016-08-24 09:53:11,766 DEBUG: View 1 : 0.539877300613
+2016-08-24 09:53:11,804 DEBUG: View 2 : 0.478527607362
+2016-08-24 09:53:11,812 DEBUG: View 3 : 0.429447852761
+2016-08-24 09:53:12,066 DEBUG: Best view : MiRNA__
+2016-08-24 09:53:17,553 DEBUG: Start: Iteration 87
+2016-08-24 09:53:17,570 DEBUG: View 0 : 0.386503067485
+2016-08-24 09:53:17,579 DEBUG: View 1 : 0.503067484663
+2016-08-24 09:53:17,617 DEBUG: View 2 : 0.539877300613
+2016-08-24 09:53:17,625 DEBUG: View 3 : 0.490797546012
+2016-08-24 09:53:17,893 DEBUG: Best view : MiRNA__
+2016-08-24 09:53:23,454 DEBUG: Start: Iteration 88
+2016-08-24 09:53:23,472 DEBUG: View 0 : 0.423312883436
+2016-08-24 09:53:23,480 DEBUG: View 1 : 0.705521472393
+2016-08-24 09:53:23,520 DEBUG: View 2 : 0.472392638037
+2016-08-24 09:53:23,528 DEBUG: View 3 : 0.41717791411
+2016-08-24 09:53:23,792 DEBUG: Best view : MiRNA__
+2016-08-24 09:53:29,579 DEBUG: Start: Iteration 89
+2016-08-24 09:53:29,598 DEBUG: View 0 : 0.38036809816
+2016-08-24 09:53:29,607 DEBUG: View 1 : 0.343558282209
+2016-08-24 09:53:29,663 DEBUG: View 2 : 0.429447852761
+2016-08-24 09:53:29,671 DEBUG: View 3 : 0.435582822086
+2016-08-24 09:53:29,671 WARNING: WARNING: All bad for iteration 88
+2016-08-24 09:53:29,966 DEBUG: Best view : Clinic_
+2016-08-24 09:53:35,846 DEBUG: Start: Iteration 90
+2016-08-24 09:53:35,863 DEBUG: View 0 : 0.601226993865
+2016-08-24 09:53:35,871 DEBUG: View 1 : 0.644171779141
+2016-08-24 09:53:35,919 DEBUG: View 2 : 0.478527607362
+2016-08-24 09:53:35,927 DEBUG: View 3 : 0.61963190184
+2016-08-24 09:53:36,194 DEBUG: Best view : MiRNA__
+2016-08-24 09:53:41,790 DEBUG: Start: Iteration 91
+2016-08-24 09:53:41,807 DEBUG: View 0 : 0.613496932515
+2016-08-24 09:53:41,815 DEBUG: View 1 : 0.558282208589
+2016-08-24 09:53:41,852 DEBUG: View 2 : 0.588957055215
+2016-08-24 09:53:41,860 DEBUG: View 3 : 0.441717791411
+2016-08-24 09:53:42,117 DEBUG: Best view : Methyl_
+2016-08-24 09:53:47,786 DEBUG: Start: Iteration 92
+2016-08-24 09:53:47,803 DEBUG: View 0 : 0.668711656442
+2016-08-24 09:53:47,811 DEBUG: View 1 : 0.515337423313
+2016-08-24 09:53:47,848 DEBUG: View 2 : 0.638036809816
+2016-08-24 09:53:47,856 DEBUG: View 3 : 0.38036809816
+2016-08-24 09:53:48,114 DEBUG: Best view : Methyl_
+2016-08-24 09:53:53,801 DEBUG: Start: Iteration 93
+2016-08-24 09:53:53,818 DEBUG: View 0 : 0.552147239264
+2016-08-24 09:53:53,825 DEBUG: View 1 : 0.631901840491
+2016-08-24 09:53:53,863 DEBUG: View 2 : 0.558282208589
+2016-08-24 09:53:53,871 DEBUG: View 3 : 0.447852760736
+2016-08-24 09:53:54,140 DEBUG: Best view : MiRNA__
+2016-08-24 09:53:59,928 DEBUG: Start: Iteration 94
+2016-08-24 09:53:59,945 DEBUG: View 0 : 0.460122699387
+2016-08-24 09:53:59,953 DEBUG: View 1 : 0.638036809816
+2016-08-24 09:53:59,990 DEBUG: View 2 : 0.576687116564
+2016-08-24 09:53:59,998 DEBUG: View 3 : 0.398773006135
+2016-08-24 09:54:00,264 DEBUG: Best view : MiRNA__
+2016-08-24 09:54:06,103 DEBUG: Start: Iteration 95
+2016-08-24 09:54:06,120 DEBUG: View 0 : 0.59509202454
+2016-08-24 09:54:06,128 DEBUG: View 1 : 0.638036809816
+2016-08-24 09:54:06,165 DEBUG: View 2 : 0.429447852761
+2016-08-24 09:54:06,173 DEBUG: View 3 : 0.496932515337
+2016-08-24 09:54:06,440 DEBUG: Best view : MiRNA__
+2016-08-24 09:54:12,344 DEBUG: Start: Iteration 96
+2016-08-24 09:54:12,361 DEBUG: View 0 : 0.601226993865
+2016-08-24 09:54:12,368 DEBUG: View 1 : 0.521472392638
+2016-08-24 09:54:12,406 DEBUG: View 2 : 0.58282208589
+2016-08-24 09:54:12,414 DEBUG: View 3 : 0.533742331288
+2016-08-24 09:54:12,683 DEBUG: Best view : Methyl_
+2016-08-24 09:54:18,660 DEBUG: Start: Iteration 97
+2016-08-24 09:54:18,677 DEBUG: View 0 : 0.374233128834
+2016-08-24 09:54:18,684 DEBUG: View 1 : 0.742331288344
+2016-08-24 09:54:18,722 DEBUG: View 2 : 0.423312883436
+2016-08-24 09:54:18,730 DEBUG: View 3 : 0.638036809816
+2016-08-24 09:54:19,002 DEBUG: Best view : MiRNA__
+2016-08-24 09:54:25,028 DEBUG: Start: Iteration 98
+2016-08-24 09:54:25,045 DEBUG: View 0 : 0.355828220859
+2016-08-24 09:54:25,053 DEBUG: View 1 : 0.558282208589
+2016-08-24 09:54:25,096 DEBUG: View 2 : 0.472392638037
+2016-08-24 09:54:25,104 DEBUG: View 3 : 0.558282208589
+2016-08-24 09:54:25,377 DEBUG: Best view : MiRNA__
+2016-08-24 09:54:31,445 DEBUG: Start: Iteration 99
+2016-08-24 09:54:31,462 DEBUG: View 0 : 0.58282208589
+2016-08-24 09:54:31,469 DEBUG: View 1 : 0.58282208589
+2016-08-24 09:54:31,507 DEBUG: View 2 : 0.58282208589
+2016-08-24 09:54:31,515 DEBUG: View 3 : 0.564417177914
+2016-08-24 09:54:31,788 DEBUG: Best view : Methyl_
+2016-08-24 09:54:37,994 DEBUG: Start: Iteration 100
+2016-08-24 09:54:38,010 DEBUG: View 0 : 0.496932515337
+2016-08-24 09:54:38,018 DEBUG: View 1 : 0.546012269939
+2016-08-24 09:54:38,056 DEBUG: View 2 : 0.521472392638
+2016-08-24 09:54:38,064 DEBUG: View 3 : 0.40490797546
+2016-08-24 09:54:38,339 DEBUG: Best view : MiRNA__
+2016-08-24 09:54:44,470 DEBUG: Start: Iteration 101
+2016-08-24 09:54:44,487 DEBUG: View 0 : 0.490797546012
+2016-08-24 09:54:44,495 DEBUG: View 1 : 0.533742331288
+2016-08-24 09:54:44,532 DEBUG: View 2 : 0.490797546012
+2016-08-24 09:54:44,539 DEBUG: View 3 : 0.546012269939
+2016-08-24 09:54:44,817 DEBUG: Best view : MiRNA__
+2016-08-24 09:54:51,232 DEBUG: Start: Iteration 102
+2016-08-24 09:54:51,252 DEBUG: View 0 : 0.300613496933
+2016-08-24 09:54:51,261 DEBUG: View 1 : 0.368098159509
+2016-08-24 09:54:51,315 DEBUG: View 2 : 0.509202453988
+2016-08-24 09:54:51,324 DEBUG: View 3 : 0.60736196319
+2016-08-24 09:54:51,621 DEBUG: Best view : Clinic_
+2016-08-24 09:54:57,874 INFO: Start: Classification
+2016-08-24 09:55:12,569 INFO: Done: Fold number 1
+2016-08-24 09:55:12,569 INFO: Start: Fold number 2
+2016-08-24 09:55:14,073 DEBUG: Start: Iteration 1
+2016-08-24 09:55:14,088 DEBUG: View 0 : 0.602649006623
+2016-08-24 09:55:14,095 DEBUG: View 1 : 0.602649006623
+2016-08-24 09:55:14,126 DEBUG: View 2 : 0.602649006623
+2016-08-24 09:55:14,133 DEBUG: View 3 : 0.602649006623
+2016-08-24 09:55:14,172 DEBUG: Best view : Methyl_
+2016-08-24 09:55:14,242 DEBUG: Start: Iteration 2
+2016-08-24 09:55:14,258 DEBUG: View 0 : 0.331125827815
+2016-08-24 09:55:14,265 DEBUG: View 1 : 0.251655629139
+2016-08-24 09:55:14,301 DEBUG: View 2 : 0.390728476821
+2016-08-24 09:55:14,308 DEBUG: View 3 : 0.384105960265
+2016-08-24 09:55:14,308 WARNING: WARNING: All bad for iteration 1
+2016-08-24 09:55:14,351 DEBUG: Best view : RANSeq_
+2016-08-24 09:55:14,492 DEBUG: Start: Iteration 3
+2016-08-24 09:55:14,508 DEBUG: View 0 : 0.53642384106
+2016-08-24 09:55:14,515 DEBUG: View 1 : 0.735099337748
+2016-08-24 09:55:14,550 DEBUG: View 2 : 0.516556291391
+2016-08-24 09:55:14,558 DEBUG: View 3 : 0.456953642384
+2016-08-24 09:55:14,603 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:14,797 DEBUG: Start: Iteration 4
+2016-08-24 09:55:14,813 DEBUG: View 0 : 0.814569536424
+2016-08-24 09:55:14,820 DEBUG: View 1 : 0.377483443709
+2016-08-24 09:55:14,856 DEBUG: View 2 : 0.523178807947
+2016-08-24 09:55:14,863 DEBUG: View 3 : 0.443708609272
+2016-08-24 09:55:14,916 DEBUG: Best view : Methyl_
+2016-08-24 09:55:15,168 DEBUG: Start: Iteration 5
+2016-08-24 09:55:15,184 DEBUG: View 0 : 0.609271523179
+2016-08-24 09:55:15,192 DEBUG: View 1 : 0.708609271523
+2016-08-24 09:55:15,227 DEBUG: View 2 : 0.516556291391
+2016-08-24 09:55:15,234 DEBUG: View 3 : 0.456953642384
+2016-08-24 09:55:15,288 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:15,596 DEBUG: Start: Iteration 6
+2016-08-24 09:55:15,612 DEBUG: View 0 : 0.615894039735
+2016-08-24 09:55:15,619 DEBUG: View 1 : 0.635761589404
+2016-08-24 09:55:15,654 DEBUG: View 2 : 0.503311258278
+2016-08-24 09:55:15,661 DEBUG: View 3 : 0.476821192053
+2016-08-24 09:55:15,717 DEBUG: Best view : Methyl_
+2016-08-24 09:55:16,081 DEBUG: Start: Iteration 7
+2016-08-24 09:55:16,097 DEBUG: View 0 : 0.384105960265
+2016-08-24 09:55:16,104 DEBUG: View 1 : 0.53642384106
+2016-08-24 09:55:16,140 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:55:16,147 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:55:16,206 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:16,624 DEBUG: Start: Iteration 8
+2016-08-24 09:55:16,639 DEBUG: View 0 : 0.456953642384
+2016-08-24 09:55:16,647 DEBUG: View 1 : 0.470198675497
+2016-08-24 09:55:16,682 DEBUG: View 2 : 0.450331125828
+2016-08-24 09:55:16,689 DEBUG: View 3 : 0.450331125828
+2016-08-24 09:55:16,689 WARNING: WARNING: All bad for iteration 7
+2016-08-24 09:55:16,751 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:17,223 DEBUG: Start: Iteration 9
+2016-08-24 09:55:17,239 DEBUG: View 0 : 0.456953642384
+2016-08-24 09:55:17,247 DEBUG: View 1 : 0.602649006623
+2016-08-24 09:55:17,282 DEBUG: View 2 : 0.569536423841
+2016-08-24 09:55:17,289 DEBUG: View 3 : 0.430463576159
+2016-08-24 09:55:17,353 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:17,881 DEBUG: Start: Iteration 10
+2016-08-24 09:55:17,896 DEBUG: View 0 : 0.622516556291
+2016-08-24 09:55:17,904 DEBUG: View 1 : 0.58940397351
+2016-08-24 09:55:17,939 DEBUG: View 2 : 0.543046357616
+2016-08-24 09:55:17,947 DEBUG: View 3 : 0.562913907285
+2016-08-24 09:55:18,013 DEBUG: Best view : Methyl_
+2016-08-24 09:55:18,596 DEBUG: Start: Iteration 11
+2016-08-24 09:55:18,613 DEBUG: View 0 : 0.450331125828
+2016-08-24 09:55:18,620 DEBUG: View 1 : 0.622516556291
+2016-08-24 09:55:18,655 DEBUG: View 2 : 0.41059602649
+2016-08-24 09:55:18,662 DEBUG: View 3 : 0.417218543046
+2016-08-24 09:55:18,730 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:19,382 DEBUG: Start: Iteration 12
+2016-08-24 09:55:19,398 DEBUG: View 0 : 0.562913907285
+2016-08-24 09:55:19,405 DEBUG: View 1 : 0.576158940397
+2016-08-24 09:55:19,441 DEBUG: View 2 : 0.456953642384
+2016-08-24 09:55:19,449 DEBUG: View 3 : 0.41059602649
+2016-08-24 09:55:19,519 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:20,210 DEBUG: Start: Iteration 13
+2016-08-24 09:55:20,226 DEBUG: View 0 : 0.483443708609
+2016-08-24 09:55:20,233 DEBUG: View 1 : 0.635761589404
+2016-08-24 09:55:20,269 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:55:20,276 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:55:20,349 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:21,098 DEBUG: Start: Iteration 14
+2016-08-24 09:55:21,114 DEBUG: View 0 : 0.523178807947
+2016-08-24 09:55:21,121 DEBUG: View 1 : 0.582781456954
+2016-08-24 09:55:21,157 DEBUG: View 2 : 0.470198675497
+2016-08-24 09:55:21,164 DEBUG: View 3 : 0.53642384106
+2016-08-24 09:55:21,239 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:22,041 DEBUG: Start: Iteration 15
+2016-08-24 09:55:22,056 DEBUG: View 0 : 0.350993377483
+2016-08-24 09:55:22,064 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:55:22,099 DEBUG: View 2 : 0.476821192053
+2016-08-24 09:55:22,106 DEBUG: View 3 : 0.569536423841
+2016-08-24 09:55:22,183 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:23,038 DEBUG: Start: Iteration 16
+2016-08-24 09:55:23,054 DEBUG: View 0 : 0.596026490066
+2016-08-24 09:55:23,061 DEBUG: View 1 : 0.543046357616
+2016-08-24 09:55:23,097 DEBUG: View 2 : 0.629139072848
+2016-08-24 09:55:23,104 DEBUG: View 3 : 0.649006622517
+2016-08-24 09:55:23,183 DEBUG: Best view : Clinic_
+2016-08-24 09:55:24,094 DEBUG: Start: Iteration 17
+2016-08-24 09:55:24,111 DEBUG: View 0 : 0.456953642384
+2016-08-24 09:55:24,118 DEBUG: View 1 : 0.615894039735
+2016-08-24 09:55:24,154 DEBUG: View 2 : 0.490066225166
+2016-08-24 09:55:24,161 DEBUG: View 3 : 0.516556291391
+2016-08-24 09:55:24,242 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:25,204 DEBUG: Start: Iteration 18
+2016-08-24 09:55:25,220 DEBUG: View 0 : 0.562913907285
+2016-08-24 09:55:25,227 DEBUG: View 1 : 0.450331125828
+2016-08-24 09:55:25,263 DEBUG: View 2 : 0.450331125828
+2016-08-24 09:55:25,270 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:55:25,354 DEBUG: Best view : Methyl_
+2016-08-24 09:55:26,372 DEBUG: Start: Iteration 19
+2016-08-24 09:55:26,388 DEBUG: View 0 : 0.364238410596
+2016-08-24 09:55:26,396 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:55:26,431 DEBUG: View 2 : 0.53642384106
+2016-08-24 09:55:26,438 DEBUG: View 3 : 0.529801324503
+2016-08-24 09:55:26,523 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:27,596 DEBUG: Start: Iteration 20
+2016-08-24 09:55:27,612 DEBUG: View 0 : 0.317880794702
+2016-08-24 09:55:27,620 DEBUG: View 1 : 0.403973509934
+2016-08-24 09:55:27,655 DEBUG: View 2 : 0.529801324503
+2016-08-24 09:55:27,663 DEBUG: View 3 : 0.629139072848
+2016-08-24 09:55:27,751 DEBUG: Best view : Clinic_
+2016-08-24 09:55:28,884 DEBUG: Start: Iteration 21
+2016-08-24 09:55:28,900 DEBUG: View 0 : 0.549668874172
+2016-08-24 09:55:28,907 DEBUG: View 1 : 0.649006622517
+2016-08-24 09:55:28,945 DEBUG: View 2 : 0.529801324503
+2016-08-24 09:55:28,952 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:55:29,041 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:30,227 DEBUG: Start: Iteration 22
+2016-08-24 09:55:30,243 DEBUG: View 0 : 0.483443708609
+2016-08-24 09:55:30,250 DEBUG: View 1 : 0.556291390728
+2016-08-24 09:55:30,285 DEBUG: View 2 : 0.622516556291
+2016-08-24 09:55:30,293 DEBUG: View 3 : 0.46357615894
+2016-08-24 09:55:30,385 DEBUG: Best view : RANSeq_
+2016-08-24 09:55:31,630 DEBUG: Start: Iteration 23
+2016-08-24 09:55:31,646 DEBUG: View 0 : 0.609271523179
+2016-08-24 09:55:31,653 DEBUG: View 1 : 0.629139072848
+2016-08-24 09:55:31,688 DEBUG: View 2 : 0.556291390728
+2016-08-24 09:55:31,696 DEBUG: View 3 : 0.629139072848
+2016-08-24 09:55:31,789 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:33,091 DEBUG: Start: Iteration 24
+2016-08-24 09:55:33,107 DEBUG: View 0 : 0.503311258278
+2016-08-24 09:55:33,114 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:55:33,149 DEBUG: View 2 : 0.470198675497
+2016-08-24 09:55:33,157 DEBUG: View 3 : 0.476821192053
+2016-08-24 09:55:33,252 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:34,607 DEBUG: Start: Iteration 25
+2016-08-24 09:55:34,623 DEBUG: View 0 : 0.562913907285
+2016-08-24 09:55:34,630 DEBUG: View 1 : 0.284768211921
+2016-08-24 09:55:34,666 DEBUG: View 2 : 0.556291390728
+2016-08-24 09:55:34,673 DEBUG: View 3 : 0.456953642384
+2016-08-24 09:55:34,771 DEBUG: Best view : Methyl_
+2016-08-24 09:55:36,182 DEBUG: Start: Iteration 26
+2016-08-24 09:55:36,198 DEBUG: View 0 : 0.390728476821
+2016-08-24 09:55:36,205 DEBUG: View 1 : 0.576158940397
+2016-08-24 09:55:36,241 DEBUG: View 2 : 0.390728476821
+2016-08-24 09:55:36,248 DEBUG: View 3 : 0.569536423841
+2016-08-24 09:55:36,348 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:37,816 DEBUG: Start: Iteration 27
+2016-08-24 09:55:37,832 DEBUG: View 0 : 0.377483443709
+2016-08-24 09:55:37,839 DEBUG: View 1 : 0.509933774834
+2016-08-24 09:55:37,875 DEBUG: View 2 : 0.543046357616
+2016-08-24 09:55:37,882 DEBUG: View 3 : 0.417218543046
+2016-08-24 09:55:37,984 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:39,506 DEBUG: Start: Iteration 28
+2016-08-24 09:55:39,522 DEBUG: View 0 : 0.556291390728
+2016-08-24 09:55:39,530 DEBUG: View 1 : 0.397350993377
+2016-08-24 09:55:39,565 DEBUG: View 2 : 0.576158940397
+2016-08-24 09:55:39,572 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:55:39,676 DEBUG: Best view : RANSeq_
+2016-08-24 09:55:41,263 DEBUG: Start: Iteration 29
+2016-08-24 09:55:41,279 DEBUG: View 0 : 0.655629139073
+2016-08-24 09:55:41,286 DEBUG: View 1 : 0.728476821192
+2016-08-24 09:55:41,321 DEBUG: View 2 : 0.615894039735
+2016-08-24 09:55:41,329 DEBUG: View 3 : 0.470198675497
+2016-08-24 09:55:41,436 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:43,079 DEBUG: Start: Iteration 30
+2016-08-24 09:55:43,095 DEBUG: View 0 : 0.569536423841
+2016-08-24 09:55:43,102 DEBUG: View 1 : 0.344370860927
+2016-08-24 09:55:43,137 DEBUG: View 2 : 0.470198675497
+2016-08-24 09:55:43,144 DEBUG: View 3 : 0.470198675497
+2016-08-24 09:55:43,253 DEBUG: Best view : Methyl_
+2016-08-24 09:55:44,951 DEBUG: Start: Iteration 31
+2016-08-24 09:55:44,967 DEBUG: View 0 : 0.562913907285
+2016-08-24 09:55:44,975 DEBUG: View 1 : 0.218543046358
+2016-08-24 09:55:45,009 DEBUG: View 2 : 0.53642384106
+2016-08-24 09:55:45,017 DEBUG: View 3 : 0.516556291391
+2016-08-24 09:55:45,128 DEBUG: Best view : Methyl_
+2016-08-24 09:55:46,886 DEBUG: Start: Iteration 32
+2016-08-24 09:55:46,902 DEBUG: View 0 : 0.470198675497
+2016-08-24 09:55:46,909 DEBUG: View 1 : 0.35761589404
+2016-08-24 09:55:46,944 DEBUG: View 2 : 0.509933774834
+2016-08-24 09:55:46,952 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:55:47,064 DEBUG: Best view : Clinic_
+2016-08-24 09:55:48,874 DEBUG: Start: Iteration 33
+2016-08-24 09:55:48,889 DEBUG: View 0 : 0.569536423841
+2016-08-24 09:55:48,897 DEBUG: View 1 : 0.596026490066
+2016-08-24 09:55:48,932 DEBUG: View 2 : 0.377483443709
+2016-08-24 09:55:48,939 DEBUG: View 3 : 0.556291390728
+2016-08-24 09:55:49,054 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:50,918 DEBUG: Start: Iteration 34
+2016-08-24 09:55:50,934 DEBUG: View 0 : 0.450331125828
+2016-08-24 09:55:50,942 DEBUG: View 1 : 0.549668874172
+2016-08-24 09:55:50,976 DEBUG: View 2 : 0.503311258278
+2016-08-24 09:55:50,984 DEBUG: View 3 : 0.41059602649
+2016-08-24 09:55:51,099 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:53,017 DEBUG: Start: Iteration 35
+2016-08-24 09:55:53,032 DEBUG: View 0 : 0.430463576159
+2016-08-24 09:55:53,040 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:55:53,075 DEBUG: View 2 : 0.596026490066
+2016-08-24 09:55:53,082 DEBUG: View 3 : 0.423841059603
+2016-08-24 09:55:53,199 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:55,212 DEBUG: Start: Iteration 36
+2016-08-24 09:55:55,229 DEBUG: View 0 : 0.675496688742
+2016-08-24 09:55:55,236 DEBUG: View 1 : 0.450331125828
+2016-08-24 09:55:55,271 DEBUG: View 2 : 0.576158940397
+2016-08-24 09:55:55,279 DEBUG: View 3 : 0.58940397351
+2016-08-24 09:55:55,400 DEBUG: Best view : Methyl_
+2016-08-24 09:55:57,436 DEBUG: Start: Iteration 37
+2016-08-24 09:55:57,451 DEBUG: View 0 : 0.569536423841
+2016-08-24 09:55:57,459 DEBUG: View 1 : 0.649006622517
+2016-08-24 09:55:57,494 DEBUG: View 2 : 0.543046357616
+2016-08-24 09:55:57,501 DEBUG: View 3 : 0.490066225166
+2016-08-24 09:55:57,623 DEBUG: Best view : MiRNA__
+2016-08-24 09:55:59,706 DEBUG: Start: Iteration 38
+2016-08-24 09:55:59,722 DEBUG: View 0 : 0.549668874172
+2016-08-24 09:55:59,730 DEBUG: View 1 : 0.64238410596
+2016-08-24 09:55:59,765 DEBUG: View 2 : 0.490066225166
+2016-08-24 09:55:59,773 DEBUG: View 3 : 0.403973509934
+2016-08-24 09:55:59,897 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:02,038 DEBUG: Start: Iteration 39
+2016-08-24 09:56:02,053 DEBUG: View 0 : 0.476821192053
+2016-08-24 09:56:02,061 DEBUG: View 1 : 0.622516556291
+2016-08-24 09:56:02,096 DEBUG: View 2 : 0.602649006623
+2016-08-24 09:56:02,103 DEBUG: View 3 : 0.496688741722
+2016-08-24 09:56:02,230 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:04,427 DEBUG: Start: Iteration 40
+2016-08-24 09:56:04,443 DEBUG: View 0 : 0.476821192053
+2016-08-24 09:56:04,451 DEBUG: View 1 : 0.569536423841
+2016-08-24 09:56:04,486 DEBUG: View 2 : 0.576158940397
+2016-08-24 09:56:04,493 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:56:04,621 DEBUG: Best view : RANSeq_
+2016-08-24 09:56:06,880 DEBUG: Start: Iteration 41
+2016-08-24 09:56:06,896 DEBUG: View 0 : 0.556291390728
+2016-08-24 09:56:06,903 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:56:06,939 DEBUG: View 2 : 0.596026490066
+2016-08-24 09:56:06,946 DEBUG: View 3 : 0.569536423841
+2016-08-24 09:56:07,075 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:09,389 DEBUG: Start: Iteration 42
+2016-08-24 09:56:09,405 DEBUG: View 0 : 0.543046357616
+2016-08-24 09:56:09,413 DEBUG: View 1 : 0.344370860927
+2016-08-24 09:56:09,448 DEBUG: View 2 : 0.437086092715
+2016-08-24 09:56:09,455 DEBUG: View 3 : 0.490066225166
+2016-08-24 09:56:09,587 DEBUG: Best view : Methyl_
+2016-08-24 09:56:11,958 DEBUG: Start: Iteration 43
+2016-08-24 09:56:11,973 DEBUG: View 0 : 0.596026490066
+2016-08-24 09:56:11,981 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:56:12,016 DEBUG: View 2 : 0.456953642384
+2016-08-24 09:56:12,024 DEBUG: View 3 : 0.556291390728
+2016-08-24 09:56:12,158 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:14,594 DEBUG: Start: Iteration 44
+2016-08-24 09:56:14,610 DEBUG: View 0 : 0.430463576159
+2016-08-24 09:56:14,617 DEBUG: View 1 : 0.483443708609
+2016-08-24 09:56:14,653 DEBUG: View 2 : 0.430463576159
+2016-08-24 09:56:14,660 DEBUG: View 3 : 0.476821192053
+2016-08-24 09:56:14,660 WARNING: WARNING: All bad for iteration 43
+2016-08-24 09:56:14,797 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:17,274 DEBUG: Start: Iteration 45
+2016-08-24 09:56:17,291 DEBUG: View 0 : 0.470198675497
+2016-08-24 09:56:17,298 DEBUG: View 1 : 0.443708609272
+2016-08-24 09:56:17,333 DEBUG: View 2 : 0.58940397351
+2016-08-24 09:56:17,341 DEBUG: View 3 : 0.496688741722
+2016-08-24 09:56:17,480 DEBUG: Best view : RANSeq_
+2016-08-24 09:56:20,029 DEBUG: Start: Iteration 46
+2016-08-24 09:56:20,045 DEBUG: View 0 : 0.496688741722
+2016-08-24 09:56:20,052 DEBUG: View 1 : 0.576158940397
+2016-08-24 09:56:20,088 DEBUG: View 2 : 0.423841059603
+2016-08-24 09:56:20,095 DEBUG: View 3 : 0.423841059603
+2016-08-24 09:56:20,235 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:22,835 DEBUG: Start: Iteration 47
+2016-08-24 09:56:22,851 DEBUG: View 0 : 0.337748344371
+2016-08-24 09:56:22,858 DEBUG: View 1 : 0.145695364238
+2016-08-24 09:56:22,894 DEBUG: View 2 : 0.523178807947
+2016-08-24 09:56:22,901 DEBUG: View 3 : 0.556291390728
+2016-08-24 09:56:23,043 DEBUG: Best view : Clinic_
+2016-08-24 09:56:25,695 DEBUG: Start: Iteration 48
+2016-08-24 09:56:25,710 DEBUG: View 0 : 0.476821192053
+2016-08-24 09:56:25,718 DEBUG: View 1 : 0.35761589404
+2016-08-24 09:56:25,753 DEBUG: View 2 : 0.483443708609
+2016-08-24 09:56:25,760 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:56:25,906 DEBUG: Best view : Clinic_
+2016-08-24 09:56:28,607 DEBUG: Start: Iteration 49
+2016-08-24 09:56:28,623 DEBUG: View 0 : 0.390728476821
+2016-08-24 09:56:28,631 DEBUG: View 1 : 0.668874172185
+2016-08-24 09:56:28,665 DEBUG: View 2 : 0.490066225166
+2016-08-24 09:56:28,673 DEBUG: View 3 : 0.490066225166
+2016-08-24 09:56:28,820 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:31,591 DEBUG: Start: Iteration 50
+2016-08-24 09:56:31,607 DEBUG: View 0 : 0.46357615894
+2016-08-24 09:56:31,614 DEBUG: View 1 : 0.496688741722
+2016-08-24 09:56:31,651 DEBUG: View 2 : 0.516556291391
+2016-08-24 09:56:31,658 DEBUG: View 3 : 0.496688741722
+2016-08-24 09:56:31,807 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:34,616 DEBUG: Start: Iteration 51
+2016-08-24 09:56:34,632 DEBUG: View 0 : 0.529801324503
+2016-08-24 09:56:34,639 DEBUG: View 1 : 0.609271523179
+2016-08-24 09:56:34,674 DEBUG: View 2 : 0.569536423841
+2016-08-24 09:56:34,682 DEBUG: View 3 : 0.46357615894
+2016-08-24 09:56:34,832 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:37,700 DEBUG: Start: Iteration 52
+2016-08-24 09:56:37,715 DEBUG: View 0 : 0.516556291391
+2016-08-24 09:56:37,723 DEBUG: View 1 : 0.337748344371
+2016-08-24 09:56:37,758 DEBUG: View 2 : 0.596026490066
+2016-08-24 09:56:37,765 DEBUG: View 3 : 0.58940397351
+2016-08-24 09:56:37,918 DEBUG: Best view : RANSeq_
+2016-08-24 09:56:40,853 DEBUG: Start: Iteration 53
+2016-08-24 09:56:40,869 DEBUG: View 0 : 0.503311258278
+2016-08-24 09:56:40,877 DEBUG: View 1 : 0.53642384106
+2016-08-24 09:56:40,913 DEBUG: View 2 : 0.490066225166
+2016-08-24 09:56:40,920 DEBUG: View 3 : 0.403973509934
+2016-08-24 09:56:41,076 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:44,061 DEBUG: Start: Iteration 54
+2016-08-24 09:56:44,077 DEBUG: View 0 : 0.576158940397
+2016-08-24 09:56:44,085 DEBUG: View 1 : 0.509933774834
+2016-08-24 09:56:44,120 DEBUG: View 2 : 0.430463576159
+2016-08-24 09:56:44,128 DEBUG: View 3 : 0.456953642384
+2016-08-24 09:56:44,286 DEBUG: Best view : Methyl_
+2016-08-24 09:56:47,328 DEBUG: Start: Iteration 55
+2016-08-24 09:56:47,344 DEBUG: View 0 : 0.483443708609
+2016-08-24 09:56:47,351 DEBUG: View 1 : 0.317880794702
+2016-08-24 09:56:47,387 DEBUG: View 2 : 0.622516556291
+2016-08-24 09:56:47,394 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:56:47,552 DEBUG: Best view : RANSeq_
+2016-08-24 09:56:50,670 DEBUG: Start: Iteration 56
+2016-08-24 09:56:50,686 DEBUG: View 0 : 0.53642384106
+2016-08-24 09:56:50,693 DEBUG: View 1 : 0.53642384106
+2016-08-24 09:56:50,728 DEBUG: View 2 : 0.622516556291
+2016-08-24 09:56:50,736 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:56:50,897 DEBUG: Best view : RANSeq_
+2016-08-24 09:56:54,078 DEBUG: Start: Iteration 57
+2016-08-24 09:56:54,094 DEBUG: View 0 : 0.53642384106
+2016-08-24 09:56:54,102 DEBUG: View 1 : 0.708609271523
+2016-08-24 09:56:54,137 DEBUG: View 2 : 0.450331125828
+2016-08-24 09:56:54,144 DEBUG: View 3 : 0.523178807947
+2016-08-24 09:56:54,307 DEBUG: Best view : MiRNA__
+2016-08-24 09:56:57,540 DEBUG: Start: Iteration 58
+2016-08-24 09:56:57,556 DEBUG: View 0 : 0.582781456954
+2016-08-24 09:56:57,563 DEBUG: View 1 : 0.602649006623
+2016-08-24 09:56:57,598 DEBUG: View 2 : 0.576158940397
+2016-08-24 09:56:57,605 DEBUG: View 3 : 0.496688741722
+2016-08-24 09:56:57,771 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:01,055 DEBUG: Start: Iteration 59
+2016-08-24 09:57:01,071 DEBUG: View 0 : 0.615894039735
+2016-08-24 09:57:01,078 DEBUG: View 1 : 0.284768211921
+2016-08-24 09:57:01,114 DEBUG: View 2 : 0.569536423841
+2016-08-24 09:57:01,121 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:57:01,288 DEBUG: Best view : Methyl_
+2016-08-24 09:57:04,633 DEBUG: Start: Iteration 60
+2016-08-24 09:57:04,648 DEBUG: View 0 : 0.543046357616
+2016-08-24 09:57:04,656 DEBUG: View 1 : 0.615894039735
+2016-08-24 09:57:04,691 DEBUG: View 2 : 0.582781456954
+2016-08-24 09:57:04,699 DEBUG: View 3 : 0.582781456954
+2016-08-24 09:57:04,868 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:08,269 DEBUG: Start: Iteration 61
+2016-08-24 09:57:08,284 DEBUG: View 0 : 0.529801324503
+2016-08-24 09:57:08,291 DEBUG: View 1 : 0.715231788079
+2016-08-24 09:57:08,327 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:57:08,334 DEBUG: View 3 : 0.423841059603
+2016-08-24 09:57:08,506 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:11,957 DEBUG: Start: Iteration 62
+2016-08-24 09:57:11,973 DEBUG: View 0 : 0.523178807947
+2016-08-24 09:57:11,980 DEBUG: View 1 : 0.350993377483
+2016-08-24 09:57:12,023 DEBUG: View 2 : 0.456953642384
+2016-08-24 09:57:12,030 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:57:12,204 DEBUG: Best view : Methyl_
+2016-08-24 09:57:15,727 DEBUG: Start: Iteration 63
+2016-08-24 09:57:15,743 DEBUG: View 0 : 0.331125827815
+2016-08-24 09:57:15,750 DEBUG: View 1 : 0.688741721854
+2016-08-24 09:57:15,785 DEBUG: View 2 : 0.64238410596
+2016-08-24 09:57:15,793 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:57:15,968 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:19,529 DEBUG: Start: Iteration 64
+2016-08-24 09:57:19,545 DEBUG: View 0 : 0.58940397351
+2016-08-24 09:57:19,552 DEBUG: View 1 : 0.596026490066
+2016-08-24 09:57:19,591 DEBUG: View 2 : 0.503311258278
+2016-08-24 09:57:19,598 DEBUG: View 3 : 0.596026490066
+2016-08-24 09:57:19,775 DEBUG: Best view : Methyl_
+2016-08-24 09:57:23,387 DEBUG: Start: Iteration 65
+2016-08-24 09:57:23,403 DEBUG: View 0 : 0.470198675497
+2016-08-24 09:57:23,411 DEBUG: View 1 : 0.41059602649
+2016-08-24 09:57:23,446 DEBUG: View 2 : 0.523178807947
+2016-08-24 09:57:23,454 DEBUG: View 3 : 0.417218543046
+2016-08-24 09:57:23,632 DEBUG: Best view : RANSeq_
+2016-08-24 09:57:27,319 DEBUG: Start: Iteration 66
+2016-08-24 09:57:27,335 DEBUG: View 0 : 0.728476821192
+2016-08-24 09:57:27,343 DEBUG: View 1 : 0.523178807947
+2016-08-24 09:57:27,379 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:57:27,386 DEBUG: View 3 : 0.41059602649
+2016-08-24 09:57:27,568 DEBUG: Best view : Methyl_
+2016-08-24 09:57:31,325 DEBUG: Start: Iteration 67
+2016-08-24 09:57:31,341 DEBUG: View 0 : 0.450331125828
+2016-08-24 09:57:31,348 DEBUG: View 1 : 0.649006622517
+2016-08-24 09:57:31,383 DEBUG: View 2 : 0.569536423841
+2016-08-24 09:57:31,391 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:57:31,574 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:35,371 DEBUG: Start: Iteration 68
+2016-08-24 09:57:35,386 DEBUG: View 0 : 0.443708609272
+2016-08-24 09:57:35,394 DEBUG: View 1 : 0.509933774834
+2016-08-24 09:57:35,429 DEBUG: View 2 : 0.635761589404
+2016-08-24 09:57:35,436 DEBUG: View 3 : 0.46357615894
+2016-08-24 09:57:35,622 DEBUG: Best view : RANSeq_
+2016-08-24 09:57:39,510 DEBUG: Start: Iteration 69
+2016-08-24 09:57:39,526 DEBUG: View 0 : 0.344370860927
+2016-08-24 09:57:39,533 DEBUG: View 1 : 0.708609271523
+2016-08-24 09:57:39,568 DEBUG: View 2 : 0.423841059603
+2016-08-24 09:57:39,576 DEBUG: View 3 : 0.417218543046
+2016-08-24 09:57:39,765 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:43,687 DEBUG: Start: Iteration 70
+2016-08-24 09:57:43,703 DEBUG: View 0 : 0.701986754967
+2016-08-24 09:57:43,711 DEBUG: View 1 : 0.483443708609
+2016-08-24 09:57:43,746 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:57:43,753 DEBUG: View 3 : 0.470198675497
+2016-08-24 09:57:43,943 DEBUG: Best view : Methyl_
+2016-08-24 09:57:47,935 DEBUG: Start: Iteration 71
+2016-08-24 09:57:47,951 DEBUG: View 0 : 0.569536423841
+2016-08-24 09:57:47,958 DEBUG: View 1 : 0.609271523179
+2016-08-24 09:57:47,993 DEBUG: View 2 : 0.417218543046
+2016-08-24 09:57:48,001 DEBUG: View 3 : 0.41059602649
+2016-08-24 09:57:48,193 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:52,229 DEBUG: Start: Iteration 72
+2016-08-24 09:57:52,245 DEBUG: View 0 : 0.377483443709
+2016-08-24 09:57:52,252 DEBUG: View 1 : 0.662251655629
+2016-08-24 09:57:52,290 DEBUG: View 2 : 0.569536423841
+2016-08-24 09:57:52,297 DEBUG: View 3 : 0.503311258278
+2016-08-24 09:57:52,491 DEBUG: Best view : MiRNA__
+2016-08-24 09:57:56,588 DEBUG: Start: Iteration 73
+2016-08-24 09:57:56,604 DEBUG: View 0 : 0.46357615894
+2016-08-24 09:57:56,612 DEBUG: View 1 : 0.615894039735
+2016-08-24 09:57:56,647 DEBUG: View 2 : 0.609271523179
+2016-08-24 09:57:56,654 DEBUG: View 3 : 0.403973509934
+2016-08-24 09:57:56,850 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:00,989 DEBUG: Start: Iteration 74
+2016-08-24 09:58:01,005 DEBUG: View 0 : 0.602649006623
+2016-08-24 09:58:01,012 DEBUG: View 1 : 0.741721854305
+2016-08-24 09:58:01,054 DEBUG: View 2 : 0.58940397351
+2016-08-24 09:58:01,061 DEBUG: View 3 : 0.53642384106
+2016-08-24 09:58:01,259 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:05,450 DEBUG: Start: Iteration 75
+2016-08-24 09:58:05,466 DEBUG: View 0 : 0.549668874172
+2016-08-24 09:58:05,473 DEBUG: View 1 : 0.662251655629
+2016-08-24 09:58:05,513 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:58:05,520 DEBUG: View 3 : 0.450331125828
+2016-08-24 09:58:05,721 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:09,965 DEBUG: Start: Iteration 76
+2016-08-24 09:58:09,981 DEBUG: View 0 : 0.529801324503
+2016-08-24 09:58:09,988 DEBUG: View 1 : 0.576158940397
+2016-08-24 09:58:10,029 DEBUG: View 2 : 0.569536423841
+2016-08-24 09:58:10,037 DEBUG: View 3 : 0.582781456954
+2016-08-24 09:58:10,238 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:14,540 DEBUG: Start: Iteration 77
+2016-08-24 09:58:14,556 DEBUG: View 0 : 0.503311258278
+2016-08-24 09:58:14,564 DEBUG: View 1 : 0.701986754967
+2016-08-24 09:58:14,604 DEBUG: View 2 : 0.509933774834
+2016-08-24 09:58:14,612 DEBUG: View 3 : 0.53642384106
+2016-08-24 09:58:14,817 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:19,168 DEBUG: Start: Iteration 78
+2016-08-24 09:58:19,183 DEBUG: View 0 : 0.735099337748
+2016-08-24 09:58:19,191 DEBUG: View 1 : 0.576158940397
+2016-08-24 09:58:19,233 DEBUG: View 2 : 0.609271523179
+2016-08-24 09:58:19,242 DEBUG: View 3 : 0.556291390728
+2016-08-24 09:58:19,448 DEBUG: Best view : Methyl_
+2016-08-24 09:58:23,864 DEBUG: Start: Iteration 79
+2016-08-24 09:58:23,880 DEBUG: View 0 : 0.629139072848
+2016-08-24 09:58:23,887 DEBUG: View 1 : 0.655629139073
+2016-08-24 09:58:23,929 DEBUG: View 2 : 0.423841059603
+2016-08-24 09:58:23,938 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:58:24,146 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:28,610 DEBUG: Start: Iteration 80
+2016-08-24 09:58:28,626 DEBUG: View 0 : 0.562913907285
+2016-08-24 09:58:28,633 DEBUG: View 1 : 0.622516556291
+2016-08-24 09:58:28,676 DEBUG: View 2 : 0.490066225166
+2016-08-24 09:58:28,684 DEBUG: View 3 : 0.549668874172
+2016-08-24 09:58:28,895 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:33,419 DEBUG: Start: Iteration 81
+2016-08-24 09:58:33,435 DEBUG: View 0 : 0.496688741722
+2016-08-24 09:58:33,442 DEBUG: View 1 : 0.41059602649
+2016-08-24 09:58:33,487 DEBUG: View 2 : 0.516556291391
+2016-08-24 09:58:33,495 DEBUG: View 3 : 0.576158940397
+2016-08-24 09:58:33,706 DEBUG: Best view : Clinic_
+2016-08-24 09:58:38,279 DEBUG: Start: Iteration 82
+2016-08-24 09:58:38,294 DEBUG: View 0 : 0.377483443709
+2016-08-24 09:58:38,302 DEBUG: View 1 : 0.516556291391
+2016-08-24 09:58:38,347 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:58:38,355 DEBUG: View 3 : 0.46357615894
+2016-08-24 09:58:38,570 DEBUG: Best view : RANSeq_
+2016-08-24 09:58:43,207 DEBUG: Start: Iteration 83
+2016-08-24 09:58:43,222 DEBUG: View 0 : 0.456953642384
+2016-08-24 09:58:43,230 DEBUG: View 1 : 0.46357615894
+2016-08-24 09:58:43,275 DEBUG: View 2 : 0.523178807947
+2016-08-24 09:58:43,283 DEBUG: View 3 : 0.350993377483
+2016-08-24 09:58:43,501 DEBUG: Best view : RANSeq_
+2016-08-24 09:58:48,208 DEBUG: Start: Iteration 84
+2016-08-24 09:58:48,224 DEBUG: View 0 : 0.470198675497
+2016-08-24 09:58:48,231 DEBUG: View 1 : 0.602649006623
+2016-08-24 09:58:48,276 DEBUG: View 2 : 0.41059602649
+2016-08-24 09:58:48,285 DEBUG: View 3 : 0.602649006623
+2016-08-24 09:58:48,504 DEBUG: Best view : MiRNA__
+2016-08-24 09:58:53,266 DEBUG: Start: Iteration 85
+2016-08-24 09:58:53,282 DEBUG: View 0 : 0.503311258278
+2016-08-24 09:58:53,290 DEBUG: View 1 : 0.337748344371
+2016-08-24 09:58:53,335 DEBUG: View 2 : 0.483443708609
+2016-08-24 09:58:53,344 DEBUG: View 3 : 0.483443708609
+2016-08-24 09:58:53,567 DEBUG: Best view : Methyl_
+2016-08-24 09:58:58,390 DEBUG: Start: Iteration 86
+2016-08-24 09:58:58,406 DEBUG: View 0 : 0.46357615894
+2016-08-24 09:58:58,414 DEBUG: View 1 : 0.615894039735
+2016-08-24 09:58:58,460 DEBUG: View 2 : 0.562913907285
+2016-08-24 09:58:58,469 DEBUG: View 3 : 0.476821192053
+2016-08-24 09:58:58,700 DEBUG: Best view : MiRNA__
+2016-08-24 09:59:03,579 DEBUG: Start: Iteration 87
+2016-08-24 09:59:03,595 DEBUG: View 0 : 0.622516556291
+2016-08-24 09:59:03,602 DEBUG: View 1 : 0.860927152318
+2016-08-24 09:59:03,647 DEBUG: View 2 : 0.456953642384
+2016-08-24 09:59:03,656 DEBUG: View 3 : 0.556291390728
+2016-08-24 09:59:03,881 DEBUG: Best view : MiRNA__
+2016-08-24 09:59:08,810 DEBUG: Start: Iteration 88
+2016-08-24 09:59:08,826 DEBUG: View 0 : 0.635761589404
+2016-08-24 09:59:08,833 DEBUG: View 1 : 0.403973509934
+2016-08-24 09:59:08,879 DEBUG: View 2 : 0.470198675497
+2016-08-24 09:59:08,888 DEBUG: View 3 : 0.516556291391
+2016-08-24 09:59:09,115 DEBUG: Best view : Methyl_
+2016-08-24 09:59:14,094 DEBUG: Start: Iteration 89
+2016-08-24 09:59:14,111 DEBUG: View 0 : 0.562913907285
+2016-08-24 09:59:14,118 DEBUG: View 1 : 0.735099337748
+2016-08-24 09:59:14,164 DEBUG: View 2 : 0.456953642384
+2016-08-24 09:59:14,172 DEBUG: View 3 : 0.576158940397
+2016-08-24 09:59:14,401 DEBUG: Best view : MiRNA__
+2016-08-24 09:59:19,446 DEBUG: Start: Iteration 90
+2016-08-24 09:59:19,461 DEBUG: View 0 : 0.549668874172
+2016-08-24 09:59:19,469 DEBUG: View 1 : 0.490066225166
+2016-08-24 09:59:19,515 DEBUG: View 2 : 0.509933774834
+2016-08-24 09:59:19,524 DEBUG: View 3 : 0.622516556291
+2016-08-24 09:59:19,755 DEBUG: Best view : Clinic_
+2016-08-24 09:59:24,857 DEBUG: Start: Iteration 91
+2016-08-24 09:59:24,873 DEBUG: View 0 : 0.523178807947
+2016-08-24 09:59:24,881 DEBUG: View 1 : 0.635761589404
+2016-08-24 09:59:24,926 DEBUG: View 2 : 0.609271523179
+2016-08-24 09:59:24,935 DEBUG: View 3 : 0.450331125828
+2016-08-24 09:59:25,168 DEBUG: Best view : MiRNA__
+2016-08-24 09:59:30,327 DEBUG: Start: Iteration 92
+2016-08-24 09:59:30,343 DEBUG: View 0 : 0.430463576159
+2016-08-24 09:59:30,350 DEBUG: View 1 : 0.655629139073
+2016-08-24 09:59:30,396 DEBUG: View 2 : 0.450331125828
+2016-08-24 09:59:30,405 DEBUG: View 3 : 0.476821192053
+2016-08-24 09:59:30,639 DEBUG: Best view : MiRNA__
+2016-08-24 09:59:35,851 DEBUG: Start: Iteration 93
+2016-08-24 09:59:35,867 DEBUG: View 0 : 0.596026490066
+2016-08-24 09:59:35,874 DEBUG: View 1 : 0.635761589404
+2016-08-24 09:59:35,929 DEBUG: View 2 : 0.423841059603
+2016-08-24 09:59:35,937 DEBUG: View 3 : 0.58940397351
+2016-08-24 09:59:36,174 DEBUG: Best view : MiRNA__
+2016-08-24 09:59:41,498 DEBUG: Start: Iteration 94
+2016-08-24 09:59:41,514 DEBUG: View 0 : 0.582781456954
+2016-08-24 09:59:41,522 DEBUG: View 1 : 0.562913907285
+2016-08-24 09:59:41,557 DEBUG: View 2 : 0.622516556291
+2016-08-24 09:59:41,565 DEBUG: View 3 : 0.476821192053
+2016-08-24 09:59:41,807 DEBUG: Best view : Methyl_
+2016-08-24 09:59:47,218 DEBUG: Start: Iteration 95
+2016-08-24 09:59:47,234 DEBUG: View 0 : 0.390728476821
+2016-08-24 09:59:47,242 DEBUG: View 1 : 0.430463576159
+2016-08-24 09:59:47,277 DEBUG: View 2 : 0.46357615894
+2016-08-24 09:59:47,284 DEBUG: View 3 : 0.602649006623
+2016-08-24 09:59:47,529 DEBUG: Best view : Clinic_
+2016-08-24 09:59:53,061 DEBUG: Start: Iteration 96
+2016-08-24 09:59:53,077 DEBUG: View 0 : 0.688741721854
+2016-08-24 09:59:53,085 DEBUG: View 1 : 0.556291390728
+2016-08-24 09:59:53,120 DEBUG: View 2 : 0.629139072848
+2016-08-24 09:59:53,128 DEBUG: View 3 : 0.53642384106
+2016-08-24 09:59:53,372 DEBUG: Best view : Methyl_
+2016-08-24 09:59:58,805 DEBUG: Start: Iteration 97
+2016-08-24 09:59:58,821 DEBUG: View 0 : 0.668874172185
+2016-08-24 09:59:58,828 DEBUG: View 1 : 0.443708609272
+2016-08-24 09:59:58,864 DEBUG: View 2 : 0.516556291391
+2016-08-24 09:59:58,871 DEBUG: View 3 : 0.53642384106
+2016-08-24 09:59:59,116 DEBUG: Best view : Methyl_
+2016-08-24 10:00:04,596 DEBUG: Start: Iteration 98
+2016-08-24 10:00:04,612 DEBUG: View 0 : 0.509933774834
+2016-08-24 10:00:04,620 DEBUG: View 1 : 0.675496688742
+2016-08-24 10:00:04,655 DEBUG: View 2 : 0.46357615894
+2016-08-24 10:00:04,662 DEBUG: View 3 : 0.417218543046
+2016-08-24 10:00:04,910 DEBUG: Best view : MiRNA__
+2016-08-24 10:00:10,446 DEBUG: Start: Iteration 99
+2016-08-24 10:00:10,462 DEBUG: View 0 : 0.569536423841
+2016-08-24 10:00:10,469 DEBUG: View 1 : 0.509933774834
+2016-08-24 10:00:10,505 DEBUG: View 2 : 0.476821192053
+2016-08-24 10:00:10,512 DEBUG: View 3 : 0.503311258278
+2016-08-24 10:00:10,761 DEBUG: Best view : Methyl_
+2016-08-24 10:00:16,350 DEBUG: Start: Iteration 100
+2016-08-24 10:00:16,366 DEBUG: View 0 : 0.437086092715
+2016-08-24 10:00:16,374 DEBUG: View 1 : 0.503311258278
+2016-08-24 10:00:16,409 DEBUG: View 2 : 0.417218543046
+2016-08-24 10:00:16,416 DEBUG: View 3 : 0.602649006623
+2016-08-24 10:00:16,668 DEBUG: Best view : Clinic_
+2016-08-24 10:00:22,325 DEBUG: Start: Iteration 101
+2016-08-24 10:00:22,341 DEBUG: View 0 : 0.516556291391
+2016-08-24 10:00:22,348 DEBUG: View 1 : 0.701986754967
+2016-08-24 10:00:22,384 DEBUG: View 2 : 0.483443708609
+2016-08-24 10:00:22,391 DEBUG: View 3 : 0.483443708609
+2016-08-24 10:00:22,646 DEBUG: Best view : MiRNA__
+2016-08-24 10:00:28,562 DEBUG: Start: Iteration 102
+2016-08-24 10:00:28,580 DEBUG: View 0 : 0.516556291391
+2016-08-24 10:00:28,589 DEBUG: View 1 : 0.403973509934
+2016-08-24 10:00:28,626 DEBUG: View 2 : 0.443708609272
+2016-08-24 10:00:28,633 DEBUG: View 3 : 0.443708609272
+2016-08-24 10:00:28,896 DEBUG: Best view : Methyl_
+2016-08-24 10:00:34,676 INFO: Start: Classification
+2016-08-24 10:00:48,946 INFO: Done: Fold number 2
+2016-08-24 10:00:48,947 INFO: Done: Classification
+2016-08-24 10:00:48,947 INFO: Info: Time for Classification: 788[s]
+2016-08-24 10:00:48,947 INFO: Start: Result Analysis for Mumbo
+2016-08-24 10:01:20,963 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 73.3311664568
+ -On Test : 76.2295081967
+ -On Validation : 80.0970873786
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.007 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0516503067485
+ - Percentage of time chosen : 0.926
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0545460122699
+ - Percentage of time chosen : 0.048
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0513374233129
+ - Percentage of time chosen : 0.007
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0527116564417
+ - Percentage of time chosen : 0.019
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0529801324503
+ - Percentage of time chosen : 0.922
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0560728476821
+ - Percentage of time chosen : 0.057
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0528675496689
+ - Percentage of time chosen : 0.012
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0512847682119
+ - Percentage of time chosen : 0.009
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 62.5766871166
+ Accuracy on test : 59.8360655738
+ Accuracy on validation : 52.427184466
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 61.4207938894
+ Accuracy on test : 66.393442623
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 68.0981595092
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 64.0776699029
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 73.5099337748
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.804046642
+ Accuracy on test : 70.9016393443
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 66.2576687117
+ Accuracy on test : 64.7540983607
+ Accuracy on validation : 62.1359223301
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 81.4569536424
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 74.7572815534
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 73.857311177
+ Accuracy on test : 72.5409836066
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 69.3251533742
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 67.9611650485
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 76.7155568196
+ Accuracy on test : 78.2786885246
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 68.0981595092
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 68.932038835
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 80.5825242718
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 76.1020598871
+ Accuracy on test : 80.3278688525
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 73.6196319018
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 70.8737864078
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 83.4437086093
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.5316702556
+ Accuracy on test : 79.0983606557
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 73.6196319018
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 83.4437086093
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.5316702556
+ Accuracy on test : 79.0983606557
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 76.0736196319
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.0897899484
+ Accuracy on test : 81.1475409836
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 73.6196319018
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 70.8737864078
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 81.4569536424
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 80.5825242718
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 77.5382927721
+ Accuracy on test : 78.2786885246
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 73.0061349693
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 81.4569536424
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.2315443059
+ Accuracy on test : 80.3278688525
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 70.5521472393
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 75.7281553398
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 76.821192053
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 73.6866696461
+ Accuracy on test : 77.4590163934
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 73.0061349693
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.5560476171
+ Accuracy on test : 79.5081967213
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 72.3926380368
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 82.119205298
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.2559216674
+ Accuracy on test : 77.868852459
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 71.7791411043
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.9425506846
+ Accuracy on test : 78.6885245902
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 71.1656441718
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 69.9029126214
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 84.7682119205
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 89.3203883495
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 77.9669280462
+ Accuracy on test : 76.2295081967
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 72.3926380368
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 70.8737864078
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 84.7682119205
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.5804249787
+ Accuracy on test : 77.868852459
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 72.3926380368
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 71.8446601942
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 85.4304635762
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 86.4077669903
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 78.9115508065
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+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 966
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 967
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 968
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 969
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 970
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 971
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 972
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 973
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 974
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 975
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 976
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 977
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 978
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 979
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 980
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 981
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 982
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 983
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 984
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 985
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 986
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 987
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 988
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 989
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:07:17 0:00:14
+ Fold 2 0:12:53 0:00:14
+ Total 0:20:11 0:00:28
+ So a total classification time of 0:13:08.
+
+
+2016-08-24 10:01:21,935 INFO: Done: Result Analysis
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-100121Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-100121Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..450d6bb8864e93756a693840a8d4617a48cb2648
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-100121Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-100121Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-100121Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d4524b7cad5c93d0b97531bca46a172c9385b74c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-100121Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
@@ -0,0 +1,14060 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 73.3311664568
+ -On Test : 76.2295081967
+ -On Validation : 80.0970873786
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA
+ -DecisionTree with depth 1.0, sub-sampled at 0.007 on RNASEQ
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0516503067485
+ - Percentage of time chosen : 0.926
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0545460122699
+ - Percentage of time chosen : 0.048
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0513374233129
+ - Percentage of time chosen : 0.007
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0527116564417
+ - Percentage of time chosen : 0.019
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0529801324503
+ - Percentage of time chosen : 0.922
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0560728476821
+ - Percentage of time chosen : 0.057
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0528675496689
+ - Percentage of time chosen : 0.012
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0512847682119
+ - Percentage of time chosen : 0.009
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 62.5766871166
+ Accuracy on test : 59.8360655738
+ Accuracy on validation : 52.427184466
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 61.4207938894
+ Accuracy on test : 66.393442623
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 68.0981595092
+ Accuracy on test : 68.0327868852
+ Accuracy on validation : 64.0776699029
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 73.5099337748
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.804046642
+ Accuracy on test : 70.9016393443
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 66.2576687117
+ Accuracy on test : 64.7540983607
+ Accuracy on validation : 62.1359223301
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 81.4569536424
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 74.7572815534
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 73.857311177
+ Accuracy on test : 72.5409836066
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 69.3251533742
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 67.9611650485
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 76.7155568196
+ Accuracy on test : 78.2786885246
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 68.0981595092
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 68.932038835
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 80.5825242718
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 76.1020598871
+ Accuracy on test : 80.3278688525
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 73.6196319018
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 70.8737864078
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 83.4437086093
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.5316702556
+ Accuracy on test : 79.0983606557
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 73.6196319018
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 72.8155339806
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 83.4437086093
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.5316702556
+ Accuracy on test : 79.0983606557
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 76.0736196319
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 84.1059602649
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.0897899484
+ Accuracy on test : 81.1475409836
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+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
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+ Accuracy on validation : 73.786407767
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+ - Iteration 997
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+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
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+ Accuracy on test : 72.9508196721
+ - Iteration 998
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+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
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+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
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+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
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+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 63.1901840491
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 60.2649006623
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.7275423557
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:07:17 0:00:14
+ Fold 2 0:12:53 0:00:14
+ Total 0:20:11 0:00:28
+ So a total classification time of 0:13:08.
+
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-110726-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-110726-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..31fcc1255c209af41f94916c315fd74958fdfdea
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-110726-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,390 @@
+2016-08-24 11:07:26,238 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 11:07:26,238 INFO: Info: Labels used: No, Yes
+2016-08-24 11:07:26,239 INFO: Info: Length of dataset:347
+2016-08-24 11:07:26,240 INFO: ### Main Programm for Multiview Classification
+2016-08-24 11:07:26,240 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 11:07:26,241 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 11:07:26,241 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 11:07:26,242 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 11:07:26,242 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 11:07:26,242 INFO: Done: Read Database Files
+2016-08-24 11:07:26,242 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 11:07:26,246 INFO: Done: Determine validation split
+2016-08-24 11:07:26,246 INFO: Start: Determine 2 folds
+2016-08-24 11:07:26,254 INFO: Info: Length of Learning Sets: 122
+2016-08-24 11:07:26,254 INFO: Info: Length of Testing Sets: 122
+2016-08-24 11:07:26,254 INFO: Info: Length of Validation Set: 103
+2016-08-24 11:07:26,254 INFO: Done: Determine folds
+2016-08-24 11:07:26,254 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 11:07:26,254 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 11:07:26,254 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 11:07:33,791 DEBUG: 0.558270893372Poulet
+2016-08-24 11:07:33,791 DEBUG: 0.521268011527Poulet
+2016-08-24 11:07:33,791 DEBUG: 0.521556195965Poulet
+2016-08-24 11:07:33,792 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:07:33,792 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 11:07:35,798 DEBUG: 0.530893371758Poulet
+2016-08-24 11:07:35,798 DEBUG: 0.530720461095Poulet
+2016-08-24 11:07:35,798 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:07:35,799 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 11:07:52,803 DEBUG: 0.583227665706Poulet
+2016-08-24 11:07:52,803 DEBUG: 0.569798270893Poulet
+2016-08-24 11:07:52,803 DEBUG: 0.543746397695Poulet
+2016-08-24 11:07:52,803 DEBUG: 0.520749279539Poulet
+2016-08-24 11:07:52,803 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:07:52,804 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 11:07:54,548 DEBUG: 0.559827089337Poulet
+2016-08-24 11:07:54,549 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:07:54,549 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 11:08:34,507 DEBUG: 0.561383285303Poulet
+2016-08-24 11:08:34,507 DEBUG: 0.549337175793Poulet
+2016-08-24 11:08:34,508 DEBUG: 0.511930835735Poulet
+2016-08-24 11:08:34,508 DEBUG: 0.514524495677Poulet
+2016-08-24 11:08:34,508 DEBUG: 0.514755043228Poulet
+2016-08-24 11:08:34,512 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:08:34,512 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 11:08:34,512 INFO: Start: Fold number 1
+2016-08-24 11:08:36,691 DEBUG: Start: Iteration 1
+2016-08-24 11:08:36,707 DEBUG: View 0 : 0.620253164557
+2016-08-24 11:08:36,715 DEBUG: View 1 : 0.26582278481
+2016-08-24 11:08:36,744 DEBUG: View 2 : 0.620253164557
+2016-08-24 11:08:36,751 DEBUG: View 3 : 0.569620253165
+2016-08-24 11:08:36,793 DEBUG: Best view : Clinic_
+2016-08-24 11:08:36,864 DEBUG: Start: Iteration 2
+2016-08-24 11:08:36,881 DEBUG: View 0 : 0.436708860759
+2016-08-24 11:08:36,888 DEBUG: View 1 : 0.481012658228
+2016-08-24 11:08:36,925 DEBUG: View 2 : 0.405063291139
+2016-08-24 11:08:36,932 DEBUG: View 3 : 0.626582278481
+2016-08-24 11:08:36,977 DEBUG: Best view : Clinic_
+2016-08-24 11:08:37,106 DEBUG: Start: Iteration 3
+2016-08-24 11:08:37,122 DEBUG: View 0 : 0.53164556962
+2016-08-24 11:08:37,130 DEBUG: View 1 : 0.626582278481
+2016-08-24 11:08:37,168 DEBUG: View 2 : 0.518987341772
+2016-08-24 11:08:37,176 DEBUG: View 3 : 0.575949367089
+2016-08-24 11:08:37,230 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:37,420 DEBUG: Start: Iteration 4
+2016-08-24 11:08:37,437 DEBUG: View 0 : 0.677215189873
+2016-08-24 11:08:37,445 DEBUG: View 1 : 0.588607594937
+2016-08-24 11:08:37,482 DEBUG: View 2 : 0.436708860759
+2016-08-24 11:08:37,489 DEBUG: View 3 : 0.411392405063
+2016-08-24 11:08:37,546 DEBUG: Best view : Methyl_
+2016-08-24 11:08:37,798 DEBUG: Start: Iteration 5
+2016-08-24 11:08:37,815 DEBUG: View 0 : 0.506329113924
+2016-08-24 11:08:37,823 DEBUG: View 1 : 0.474683544304
+2016-08-24 11:08:37,861 DEBUG: View 2 : 0.392405063291
+2016-08-24 11:08:37,868 DEBUG: View 3 : 0.436708860759
+2016-08-24 11:08:37,927 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:38,240 DEBUG: Start: Iteration 6
+2016-08-24 11:08:38,256 DEBUG: View 0 : 0.449367088608
+2016-08-24 11:08:38,264 DEBUG: View 1 : 0.626582278481
+2016-08-24 11:08:38,302 DEBUG: View 2 : 0.417721518987
+2016-08-24 11:08:38,309 DEBUG: View 3 : 0.53164556962
+2016-08-24 11:08:38,371 DEBUG: Best view : Clinic_
+2016-08-24 11:08:38,740 DEBUG: Start: Iteration 7
+2016-08-24 11:08:38,756 DEBUG: View 0 : 0.443037974684
+2016-08-24 11:08:38,764 DEBUG: View 1 : 0.487341772152
+2016-08-24 11:08:38,800 DEBUG: View 2 : 0.582278481013
+2016-08-24 11:08:38,808 DEBUG: View 3 : 0.512658227848
+2016-08-24 11:08:38,871 DEBUG: Best view : RANSeq_
+2016-08-24 11:08:39,315 DEBUG: Start: Iteration 8
+2016-08-24 11:08:39,332 DEBUG: View 0 : 0.417721518987
+2016-08-24 11:08:39,339 DEBUG: View 1 : 0.462025316456
+2016-08-24 11:08:39,377 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:08:39,384 DEBUG: View 3 : 0.556962025316
+2016-08-24 11:08:39,450 DEBUG: Best view : Clinic_
+2016-08-24 11:08:39,972 DEBUG: Start: Iteration 9
+2016-08-24 11:08:39,990 DEBUG: View 0 : 0.5
+2016-08-24 11:08:39,998 DEBUG: View 1 : 0.651898734177
+2016-08-24 11:08:40,037 DEBUG: View 2 : 0.537974683544
+2016-08-24 11:08:40,045 DEBUG: View 3 : 0.392405063291
+2016-08-24 11:08:40,115 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:40,698 DEBUG: Start: Iteration 10
+2016-08-24 11:08:40,715 DEBUG: View 0 : 0.594936708861
+2016-08-24 11:08:40,723 DEBUG: View 1 : 0.354430379747
+2016-08-24 11:08:40,760 DEBUG: View 2 : 0.613924050633
+2016-08-24 11:08:40,768 DEBUG: View 3 : 0.544303797468
+2016-08-24 11:08:40,837 DEBUG: Best view : RANSeq_
+2016-08-24 11:08:41,469 DEBUG: Start: Iteration 11
+2016-08-24 11:08:41,485 DEBUG: View 0 : 0.367088607595
+2016-08-24 11:08:41,493 DEBUG: View 1 : 0.658227848101
+2016-08-24 11:08:41,530 DEBUG: View 2 : 0.537974683544
+2016-08-24 11:08:41,537 DEBUG: View 3 : 0.582278481013
+2016-08-24 11:08:41,610 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:42,303 DEBUG: Start: Iteration 12
+2016-08-24 11:08:42,319 DEBUG: View 0 : 0.424050632911
+2016-08-24 11:08:42,327 DEBUG: View 1 : 0.373417721519
+2016-08-24 11:08:42,364 DEBUG: View 2 : 0.462025316456
+2016-08-24 11:08:42,371 DEBUG: View 3 : 0.588607594937
+2016-08-24 11:08:42,445 DEBUG: Best view : Clinic_
+2016-08-24 11:08:43,193 DEBUG: Start: Iteration 13
+2016-08-24 11:08:43,209 DEBUG: View 0 : 0.474683544304
+2016-08-24 11:08:43,217 DEBUG: View 1 : 0.575949367089
+2016-08-24 11:08:43,253 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:08:43,261 DEBUG: View 3 : 0.386075949367
+2016-08-24 11:08:43,339 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:44,142 DEBUG: Start: Iteration 14
+2016-08-24 11:08:44,159 DEBUG: View 0 : 0.620253164557
+2016-08-24 11:08:44,166 DEBUG: View 1 : 0.493670886076
+2016-08-24 11:08:44,203 DEBUG: View 2 : 0.575949367089
+2016-08-24 11:08:44,211 DEBUG: View 3 : 0.658227848101
+2016-08-24 11:08:44,291 DEBUG: Best view : Clinic_
+2016-08-24 11:08:45,149 DEBUG: Start: Iteration 15
+2016-08-24 11:08:45,165 DEBUG: View 0 : 0.518987341772
+2016-08-24 11:08:45,173 DEBUG: View 1 : 0.46835443038
+2016-08-24 11:08:45,210 DEBUG: View 2 : 0.392405063291
+2016-08-24 11:08:45,218 DEBUG: View 3 : 0.443037974684
+2016-08-24 11:08:45,299 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:46,226 DEBUG: Start: Iteration 16
+2016-08-24 11:08:46,243 DEBUG: View 0 : 0.556962025316
+2016-08-24 11:08:46,251 DEBUG: View 1 : 0.398734177215
+2016-08-24 11:08:46,287 DEBUG: View 2 : 0.550632911392
+2016-08-24 11:08:46,294 DEBUG: View 3 : 0.664556962025
+2016-08-24 11:08:46,380 DEBUG: Best view : Clinic_
+2016-08-24 11:08:47,364 DEBUG: Start: Iteration 17
+2016-08-24 11:08:47,380 DEBUG: View 0 : 0.626582278481
+2016-08-24 11:08:47,389 DEBUG: View 1 : 0.506329113924
+2016-08-24 11:08:47,428 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:08:47,436 DEBUG: View 3 : 0.455696202532
+2016-08-24 11:08:47,522 DEBUG: Best view : Methyl_
+2016-08-24 11:08:48,613 DEBUG: Start: Iteration 18
+2016-08-24 11:08:48,629 DEBUG: View 0 : 0.525316455696
+2016-08-24 11:08:48,636 DEBUG: View 1 : 0.715189873418
+2016-08-24 11:08:48,673 DEBUG: View 2 : 0.386075949367
+2016-08-24 11:08:48,681 DEBUG: View 3 : 0.455696202532
+2016-08-24 11:08:48,770 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:49,927 DEBUG: Start: Iteration 19
+2016-08-24 11:08:49,947 DEBUG: View 0 : 0.550632911392
+2016-08-24 11:08:49,955 DEBUG: View 1 : 0.569620253165
+2016-08-24 11:08:49,992 DEBUG: View 2 : 0.405063291139
+2016-08-24 11:08:50,000 DEBUG: View 3 : 0.575949367089
+2016-08-24 11:08:50,090 DEBUG: Best view : Clinic_
+2016-08-24 11:08:51,285 DEBUG: Start: Iteration 20
+2016-08-24 11:08:51,304 DEBUG: View 0 : 0.424050632911
+2016-08-24 11:08:51,313 DEBUG: View 1 : 0.354430379747
+2016-08-24 11:08:51,355 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:08:51,363 DEBUG: View 3 : 0.436708860759
+2016-08-24 11:08:51,363 WARNING: WARNING: All bad for iteration 19
+2016-08-24 11:08:51,460 DEBUG: Best view : RANSeq_
+2016-08-24 11:08:52,684 DEBUG: Start: Iteration 21
+2016-08-24 11:08:52,701 DEBUG: View 0 : 0.563291139241
+2016-08-24 11:08:52,708 DEBUG: View 1 : 0.29746835443
+2016-08-24 11:08:52,745 DEBUG: View 2 : 0.487341772152
+2016-08-24 11:08:52,753 DEBUG: View 3 : 0.462025316456
+2016-08-24 11:08:52,849 DEBUG: Best view : Methyl_
+2016-08-24 11:08:54,166 DEBUG: Start: Iteration 22
+2016-08-24 11:08:54,182 DEBUG: View 0 : 0.563291139241
+2016-08-24 11:08:54,190 DEBUG: View 1 : 0.392405063291
+2016-08-24 11:08:54,232 DEBUG: View 2 : 0.518987341772
+2016-08-24 11:08:54,239 DEBUG: View 3 : 0.658227848101
+2016-08-24 11:08:54,339 DEBUG: Best view : Clinic_
+2016-08-24 11:08:55,764 DEBUG: Start: Iteration 23
+2016-08-24 11:08:55,784 DEBUG: View 0 : 0.405063291139
+2016-08-24 11:08:55,796 DEBUG: View 1 : 0.696202531646
+2016-08-24 11:08:55,833 DEBUG: View 2 : 0.512658227848
+2016-08-24 11:08:55,840 DEBUG: View 3 : 0.481012658228
+2016-08-24 11:08:55,941 DEBUG: Best view : MiRNA__
+2016-08-24 11:08:57,391 DEBUG: Start: Iteration 24
+2016-08-24 11:08:57,408 DEBUG: View 0 : 0.563291139241
+2016-08-24 11:08:57,416 DEBUG: View 1 : 0.512658227848
+2016-08-24 11:08:57,455 DEBUG: View 2 : 0.626582278481
+2016-08-24 11:08:57,465 DEBUG: View 3 : 0.556962025316
+2016-08-24 11:08:57,578 DEBUG: Best view : RANSeq_
+2016-08-24 11:08:59,113 DEBUG: Start: Iteration 25
+2016-08-24 11:08:59,129 DEBUG: View 0 : 0.462025316456
+2016-08-24 11:08:59,137 DEBUG: View 1 : 0.626582278481
+2016-08-24 11:08:59,174 DEBUG: View 2 : 0.462025316456
+2016-08-24 11:08:59,181 DEBUG: View 3 : 0.474683544304
+2016-08-24 11:08:59,294 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:00,911 DEBUG: Start: Iteration 26
+2016-08-24 11:09:00,929 DEBUG: View 0 : 0.316455696203
+2016-08-24 11:09:00,937 DEBUG: View 1 : 0.29746835443
+2016-08-24 11:09:00,974 DEBUG: View 2 : 0.632911392405
+2016-08-24 11:09:00,981 DEBUG: View 3 : 0.544303797468
+2016-08-24 11:09:01,092 DEBUG: Best view : RANSeq_
+2016-08-24 11:09:02,722 DEBUG: Start: Iteration 27
+2016-08-24 11:09:02,739 DEBUG: View 0 : 0.53164556962
+2016-08-24 11:09:02,747 DEBUG: View 1 : 0.620253164557
+2016-08-24 11:09:02,783 DEBUG: View 2 : 0.594936708861
+2016-08-24 11:09:02,791 DEBUG: View 3 : 0.53164556962
+2016-08-24 11:09:02,898 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:04,562 DEBUG: Start: Iteration 28
+2016-08-24 11:09:04,579 DEBUG: View 0 : 0.398734177215
+2016-08-24 11:09:04,587 DEBUG: View 1 : 0.487341772152
+2016-08-24 11:09:04,623 DEBUG: View 2 : 0.449367088608
+2016-08-24 11:09:04,631 DEBUG: View 3 : 0.537974683544
+2016-08-24 11:09:04,742 DEBUG: Best view : Clinic_
+2016-08-24 11:09:06,650 DEBUG: Start: Iteration 29
+2016-08-24 11:09:06,666 DEBUG: View 0 : 0.544303797468
+2016-08-24 11:09:06,674 DEBUG: View 1 : 0.708860759494
+2016-08-24 11:09:06,711 DEBUG: View 2 : 0.462025316456
+2016-08-24 11:09:06,719 DEBUG: View 3 : 0.575949367089
+2016-08-24 11:09:06,836 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:08,697 DEBUG: Start: Iteration 30
+2016-08-24 11:09:08,714 DEBUG: View 0 : 0.46835443038
+2016-08-24 11:09:08,721 DEBUG: View 1 : 0.512658227848
+2016-08-24 11:09:08,759 DEBUG: View 2 : 0.424050632911
+2016-08-24 11:09:08,766 DEBUG: View 3 : 0.462025316456
+2016-08-24 11:09:08,882 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:10,855 DEBUG: Start: Iteration 31
+2016-08-24 11:09:10,874 DEBUG: View 0 : 0.563291139241
+2016-08-24 11:09:10,882 DEBUG: View 1 : 0.335443037975
+2016-08-24 11:09:10,922 DEBUG: View 2 : 0.512658227848
+2016-08-24 11:09:10,930 DEBUG: View 3 : 0.487341772152
+2016-08-24 11:09:11,065 DEBUG: Best view : Methyl_
+2016-08-24 11:09:13,022 DEBUG: Start: Iteration 32
+2016-08-24 11:09:13,039 DEBUG: View 0 : 0.424050632911
+2016-08-24 11:09:13,047 DEBUG: View 1 : 0.632911392405
+2016-08-24 11:09:13,089 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:09:13,097 DEBUG: View 3 : 0.582278481013
+2016-08-24 11:09:13,225 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:15,276 DEBUG: Start: Iteration 33
+2016-08-24 11:09:15,292 DEBUG: View 0 : 0.493670886076
+2016-08-24 11:09:15,300 DEBUG: View 1 : 0.651898734177
+2016-08-24 11:09:15,340 DEBUG: View 2 : 0.462025316456
+2016-08-24 11:09:15,349 DEBUG: View 3 : 0.367088607595
+2016-08-24 11:09:15,480 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:17,640 DEBUG: Start: Iteration 34
+2016-08-24 11:09:17,656 DEBUG: View 0 : 0.455696202532
+2016-08-24 11:09:17,664 DEBUG: View 1 : 0.79746835443
+2016-08-24 11:09:17,701 DEBUG: View 2 : 0.594936708861
+2016-08-24 11:09:17,708 DEBUG: View 3 : 0.594936708861
+2016-08-24 11:09:17,832 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:19,911 DEBUG: Start: Iteration 35
+2016-08-24 11:09:19,928 DEBUG: View 0 : 0.575949367089
+2016-08-24 11:09:19,935 DEBUG: View 1 : 0.601265822785
+2016-08-24 11:09:19,971 DEBUG: View 2 : 0.613924050633
+2016-08-24 11:09:19,979 DEBUG: View 3 : 0.443037974684
+2016-08-24 11:09:20,105 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:22,296 DEBUG: Start: Iteration 36
+2016-08-24 11:09:22,312 DEBUG: View 0 : 0.639240506329
+2016-08-24 11:09:22,320 DEBUG: View 1 : 0.550632911392
+2016-08-24 11:09:22,357 DEBUG: View 2 : 0.424050632911
+2016-08-24 11:09:22,365 DEBUG: View 3 : 0.474683544304
+2016-08-24 11:09:22,498 DEBUG: Best view : Methyl_
+2016-08-24 11:09:24,768 DEBUG: Start: Iteration 37
+2016-08-24 11:09:24,785 DEBUG: View 0 : 0.455696202532
+2016-08-24 11:09:24,792 DEBUG: View 1 : 0.677215189873
+2016-08-24 11:09:24,831 DEBUG: View 2 : 0.46835443038
+2016-08-24 11:09:24,838 DEBUG: View 3 : 0.518987341772
+2016-08-24 11:09:24,970 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:27,288 DEBUG: Start: Iteration 38
+2016-08-24 11:09:27,305 DEBUG: View 0 : 0.411392405063
+2016-08-24 11:09:27,313 DEBUG: View 1 : 0.46835443038
+2016-08-24 11:09:27,350 DEBUG: View 2 : 0.436708860759
+2016-08-24 11:09:27,357 DEBUG: View 3 : 0.474683544304
+2016-08-24 11:09:27,358 WARNING: WARNING: All bad for iteration 37
+2016-08-24 11:09:27,495 DEBUG: Best view : Clinic_
+2016-08-24 11:09:29,938 DEBUG: Start: Iteration 39
+2016-08-24 11:09:29,954 DEBUG: View 0 : 0.563291139241
+2016-08-24 11:09:29,962 DEBUG: View 1 : 0.379746835443
+2016-08-24 11:09:29,998 DEBUG: View 2 : 0.430379746835
+2016-08-24 11:09:30,006 DEBUG: View 3 : 0.443037974684
+2016-08-24 11:09:30,143 DEBUG: Best view : Methyl_
+2016-08-24 11:09:32,730 DEBUG: Start: Iteration 40
+2016-08-24 11:09:32,748 DEBUG: View 0 : 0.462025316456
+2016-08-24 11:09:32,755 DEBUG: View 1 : 0.626582278481
+2016-08-24 11:09:32,797 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:09:32,804 DEBUG: View 3 : 0.53164556962
+2016-08-24 11:09:32,941 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:35,450 DEBUG: Start: Iteration 41
+2016-08-24 11:09:35,467 DEBUG: View 0 : 0.556962025316
+2016-08-24 11:09:35,474 DEBUG: View 1 : 0.620253164557
+2016-08-24 11:09:35,511 DEBUG: View 2 : 0.443037974684
+2016-08-24 11:09:35,518 DEBUG: View 3 : 0.594936708861
+2016-08-24 11:09:35,658 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:38,266 DEBUG: Start: Iteration 42
+2016-08-24 11:09:38,283 DEBUG: View 0 : 0.632911392405
+2016-08-24 11:09:38,290 DEBUG: View 1 : 0.582278481013
+2016-08-24 11:09:38,328 DEBUG: View 2 : 0.550632911392
+2016-08-24 11:09:38,335 DEBUG: View 3 : 0.398734177215
+2016-08-24 11:09:38,481 DEBUG: Best view : Methyl_
+2016-08-24 11:09:41,096 DEBUG: Start: Iteration 43
+2016-08-24 11:09:41,113 DEBUG: View 0 : 0.430379746835
+2016-08-24 11:09:41,121 DEBUG: View 1 : 0.613924050633
+2016-08-24 11:09:41,158 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:09:41,165 DEBUG: View 3 : 0.512658227848
+2016-08-24 11:09:41,315 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:43,945 DEBUG: Start: Iteration 44
+2016-08-24 11:09:43,961 DEBUG: View 0 : 0.462025316456
+2016-08-24 11:09:43,969 DEBUG: View 1 : 0.537974683544
+2016-08-24 11:09:44,024 DEBUG: View 2 : 0.594936708861
+2016-08-24 11:09:44,038 DEBUG: View 3 : 0.411392405063
+2016-08-24 11:09:44,211 DEBUG: Best view : RANSeq_
+2016-08-24 11:09:46,944 DEBUG: Start: Iteration 45
+2016-08-24 11:09:46,961 DEBUG: View 0 : 0.53164556962
+2016-08-24 11:09:46,968 DEBUG: View 1 : 0.626582278481
+2016-08-24 11:09:47,006 DEBUG: View 2 : 0.506329113924
+2016-08-24 11:09:47,014 DEBUG: View 3 : 0.462025316456
+2016-08-24 11:09:47,164 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:49,893 DEBUG: Start: Iteration 46
+2016-08-24 11:09:49,910 DEBUG: View 0 : 0.348101265823
+2016-08-24 11:09:49,917 DEBUG: View 1 : 0.607594936709
+2016-08-24 11:09:49,954 DEBUG: View 2 : 0.632911392405
+2016-08-24 11:09:49,962 DEBUG: View 3 : 0.556962025316
+2016-08-24 11:09:50,111 DEBUG: Best view : RANSeq_
+2016-08-24 11:09:52,926 DEBUG: Start: Iteration 47
+2016-08-24 11:09:52,943 DEBUG: View 0 : 0.518987341772
+2016-08-24 11:09:52,951 DEBUG: View 1 : 0.664556962025
+2016-08-24 11:09:52,987 DEBUG: View 2 : 0.417721518987
+2016-08-24 11:09:52,995 DEBUG: View 3 : 0.582278481013
+2016-08-24 11:09:53,147 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:56,001 DEBUG: Start: Iteration 48
+2016-08-24 11:09:56,017 DEBUG: View 0 : 0.487341772152
+2016-08-24 11:09:56,025 DEBUG: View 1 : 0.689873417722
+2016-08-24 11:09:56,063 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:09:56,071 DEBUG: View 3 : 0.449367088608
+2016-08-24 11:09:56,226 DEBUG: Best view : MiRNA__
+2016-08-24 11:09:59,142 DEBUG: Start: Iteration 49
+2016-08-24 11:09:59,158 DEBUG: View 0 : 0.360759493671
+2016-08-24 11:09:59,166 DEBUG: View 1 : 0.392405063291
+2016-08-24 11:09:59,202 DEBUG: View 2 : 0.398734177215
+2016-08-24 11:09:59,210 DEBUG: View 3 : 0.607594936709
+2016-08-24 11:09:59,368 DEBUG: Best view : Clinic_
+2016-08-24 11:10:02,340 DEBUG: Start: Iteration 50
+2016-08-24 11:10:02,356 DEBUG: View 0 : 0.518987341772
+2016-08-24 11:10:02,364 DEBUG: View 1 : 0.5
+2016-08-24 11:10:02,400 DEBUG: View 2 : 0.430379746835
+2016-08-24 11:10:02,408 DEBUG: View 3 : 0.556962025316
+2016-08-24 11:10:02,569 DEBUG: Best view : MiRNA__
+2016-08-24 11:10:05,711 DEBUG: Start: Iteration 51
+2016-08-24 11:10:05,734 DEBUG: View 0 : 0.518987341772
+2016-08-24 11:10:05,747 DEBUG: View 1 : 0.373417721519
+2016-08-24 11:10:05,793 DEBUG: View 2 : 0.518987341772
+2016-08-24 11:10:05,801 DEBUG: View 3 : 0.556962025316
+2016-08-24 11:10:05,984 DEBUG: Best view : Clinic_
+2016-08-24 11:10:09,117 DEBUG: Start: Iteration 52
+2016-08-24 11:10:09,133 DEBUG: View 0 : 0.430379746835
+2016-08-24 11:10:09,141 DEBUG: View 1 : 0.645569620253
+2016-08-24 11:10:09,178 DEBUG: View 2 : 0.556962025316
+2016-08-24 11:10:09,185 DEBUG: View 3 : 0.658227848101
+2016-08-24 11:10:09,351 DEBUG: Best view : Clinic_
+2016-08-24 11:10:12,580 DEBUG: Start: Iteration 53
+2016-08-24 11:10:12,600 DEBUG: View 0 : 0.550632911392
+2016-08-24 11:10:12,609 DEBUG: View 1 : 0.639240506329
+2016-08-24 11:10:12,649 DEBUG: View 2 : 0.525316455696
+2016-08-24 11:10:12,657 DEBUG: View 3 : 0.487341772152
+2016-08-24 11:10:12,836 DEBUG: Best view : MiRNA__
+2016-08-24 11:10:16,117 DEBUG: Start: Iteration 54
+2016-08-24 11:10:16,135 DEBUG: View 0 : 0.481012658228
+2016-08-24 11:10:16,143 DEBUG: View 1 : 0.430379746835
+2016-08-24 11:10:16,180 DEBUG: View 2 : 0.607594936709
+2016-08-24 11:10:16,187 DEBUG: View 3 : 0.582278481013
+2016-08-24 11:10:16,358 DEBUG: Best view : RANSeq_
+2016-08-24 11:10:19,696 DEBUG: Start: Iteration 55
+2016-08-24 11:10:19,712 DEBUG: View 0 : 0.594936708861
+2016-08-24 11:10:19,720 DEBUG: View 1 : 0.607594936709
+2016-08-24 11:10:19,756 DEBUG: View 2 : 0.512658227848
+2016-08-24 11:10:19,764 DEBUG: View 3 : 0.5
+2016-08-24 11:10:19,935 DEBUG: Best view : Methyl_
+2016-08-24 11:10:23,272 DEBUG: Start: Iteration 56
+2016-08-24 11:10:23,289 DEBUG: View 0 : 0.563291139241
+2016-08-24 11:10:23,297 DEBUG: View 1 : 0.405063291139
+2016-08-24 11:10:23,334 DEBUG: View 2 : 0.575949367089
+2016-08-24 11:10:23,341 DEBUG: View 3 : 0.594936708861
+2016-08-24 11:10:23,515 DEBUG: Best view : Clinic_
+2016-08-24 11:10:26,942 DEBUG: Start: Iteration 57
+2016-08-24 11:10:26,959 DEBUG: View 0 : 0.481012658228
+2016-08-24 11:10:26,966 DEBUG: View 1 : 0.5
+2016-08-24 11:10:27,003 DEBUG: View 2 : 0.512658227848
+2016-08-24 11:10:27,011 DEBUG: View 3 : 0.563291139241
+2016-08-24 11:10:27,189 DEBUG: Best view : Clinic_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111030-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111030-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..eef88fa91eec1a705104f8e957e945116b464be1
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111030-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,32 @@
+2016-08-24 11:10:30,661 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 11:10:30,661 INFO: Info: Labels used: No, Yes
+2016-08-24 11:10:30,662 INFO: Info: Length of dataset:347
+2016-08-24 11:10:30,663 INFO: ### Main Programm for Multiview Classification
+2016-08-24 11:10:30,663 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 11:10:30,664 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 11:10:30,664 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 11:10:30,664 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 11:10:30,665 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 11:10:30,665 INFO: Done: Read Database Files
+2016-08-24 11:10:30,665 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 11:10:30,668 INFO: Done: Determine validation split
+2016-08-24 11:10:30,669 INFO: Start: Determine 2 folds
+2016-08-24 11:10:30,679 INFO: Info: Length of Learning Sets: 122
+2016-08-24 11:10:30,679 INFO: Info: Length of Testing Sets: 122
+2016-08-24 11:10:30,679 INFO: Info: Length of Validation Set: 103
+2016-08-24 11:10:30,679 INFO: Done: Determine folds
+2016-08-24 11:10:30,679 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 11:10:30,679 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 11:10:30,679 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 11:10:38,124 DEBUG: Info: Best Reslut : 0.515158501441
+2016-08-24 11:10:38,124 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:10:38,125 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 11:10:40,053 DEBUG: Info: Best Reslut : 0.546397694524
+2016-08-24 11:10:40,053 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:10:40,053 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 11:10:57,326 DEBUG: Info: Best Reslut : 0.501268011527
+2016-08-24 11:10:57,327 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:10:57,327 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 11:10:59,071 DEBUG: Info: Best Reslut : 0.510086455331
+2016-08-24 11:10:59,072 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:10:59,072 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111136-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111136-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..30b218573d57c9089f6b925e93d4e4a0f0836842
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111136-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,391 @@
+2016-08-24 11:11:36,038 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 11:11:36,039 INFO: Info: Labels used: No, Yes
+2016-08-24 11:11:36,039 INFO: Info: Length of dataset:347
+2016-08-24 11:11:36,040 INFO: ### Main Programm for Multiview Classification
+2016-08-24 11:11:36,041 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 11:11:36,041 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 11:11:36,041 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 11:11:36,042 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 11:11:36,042 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 11:11:36,042 INFO: Done: Read Database Files
+2016-08-24 11:11:36,043 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 11:11:36,046 INFO: Done: Determine validation split
+2016-08-24 11:11:36,046 INFO: Start: Determine 2 folds
+2016-08-24 11:11:36,054 INFO: Info: Length of Learning Sets: 122
+2016-08-24 11:11:36,054 INFO: Info: Length of Testing Sets: 122
+2016-08-24 11:11:36,054 INFO: Info: Length of Validation Set: 103
+2016-08-24 11:11:36,054 INFO: Done: Determine folds
+2016-08-24 11:11:36,054 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 11:11:36,054 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 11:11:36,055 DEBUG: Start: Gridsearch for DecisionTree on Methyl_
+2016-08-24 11:11:43,470 DEBUG: Info: Best Reslut : 0.506570605187
+2016-08-24 11:11:43,470 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:11:43,470 DEBUG: Start: Gridsearch for DecisionTree on MiRNA__
+2016-08-24 11:11:45,393 DEBUG: Info: Best Reslut : 0.596080691643
+2016-08-24 11:11:45,393 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:11:45,394 DEBUG: Start: Gridsearch for DecisionTree on RANSeq_
+2016-08-24 11:12:02,118 DEBUG: Info: Best Reslut : 0.520922190202
+2016-08-24 11:12:02,119 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:12:02,119 DEBUG: Start: Gridsearch for DecisionTree on Clinic_
+2016-08-24 11:12:03,876 DEBUG: Info: Best Reslut : 0.504553314121
+2016-08-24 11:12:03,877 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:12:03,877 DEBUG: Start: Gridsearch for DecisionTree on MRNASeq
+2016-08-24 11:12:41,748 DEBUG: Info: Best Reslut : 0.515216138329
+2016-08-24 11:12:41,749 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 11:12:41,749 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 11:12:41,749 INFO: Start: Fold number 1
+2016-08-24 11:12:43,406 DEBUG: Start: Iteration 1
+2016-08-24 11:12:43,425 DEBUG: View 0 : 0.639240506329
+2016-08-24 11:12:43,433 DEBUG: View 1 : 0.620253164557
+2016-08-24 11:12:43,471 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:12:43,479 DEBUG: View 3 : 0.379746835443
+2016-08-24 11:12:43,520 DEBUG: Best view : Methyl_
+2016-08-24 11:12:43,596 DEBUG: Start: Iteration 2
+2016-08-24 11:12:43,614 DEBUG: View 0 : 0.620253164557
+2016-08-24 11:12:43,621 DEBUG: View 1 : 0.398734177215
+2016-08-24 11:12:43,658 DEBUG: View 2 : 0.398734177215
+2016-08-24 11:12:43,666 DEBUG: View 3 : 0.518987341772
+2016-08-24 11:12:43,711 DEBUG: Best view : Methyl_
+2016-08-24 11:12:43,849 DEBUG: Start: Iteration 3
+2016-08-24 11:12:43,866 DEBUG: View 0 : 0.569620253165
+2016-08-24 11:12:43,874 DEBUG: View 1 : 0.436708860759
+2016-08-24 11:12:43,911 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:12:43,918 DEBUG: View 3 : 0.430379746835
+2016-08-24 11:12:43,972 DEBUG: Best view : Methyl_
+2016-08-24 11:12:44,173 DEBUG: Start: Iteration 4
+2016-08-24 11:12:44,189 DEBUG: View 0 : 0.575949367089
+2016-08-24 11:12:44,197 DEBUG: View 1 : 0.512658227848
+2016-08-24 11:12:44,234 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:12:44,242 DEBUG: View 3 : 0.411392405063
+2016-08-24 11:12:44,298 DEBUG: Best view : Methyl_
+2016-08-24 11:12:44,560 DEBUG: Start: Iteration 5
+2016-08-24 11:12:44,576 DEBUG: View 0 : 0.759493670886
+2016-08-24 11:12:44,584 DEBUG: View 1 : 0.569620253165
+2016-08-24 11:12:44,621 DEBUG: View 2 : 0.398734177215
+2016-08-24 11:12:44,628 DEBUG: View 3 : 0.518987341772
+2016-08-24 11:12:44,687 DEBUG: Best view : Methyl_
+2016-08-24 11:12:45,011 DEBUG: Start: Iteration 6
+2016-08-24 11:12:45,027 DEBUG: View 0 : 0.474683544304
+2016-08-24 11:12:45,035 DEBUG: View 1 : 0.46835443038
+2016-08-24 11:12:45,072 DEBUG: View 2 : 0.601265822785
+2016-08-24 11:12:45,080 DEBUG: View 3 : 0.53164556962
+2016-08-24 11:12:45,140 DEBUG: Best view : RANSeq_
+2016-08-24 11:12:45,549 DEBUG: Start: Iteration 7
+2016-08-24 11:12:45,565 DEBUG: View 0 : 0.620253164557
+2016-08-24 11:12:45,574 DEBUG: View 1 : 0.392405063291
+2016-08-24 11:12:45,610 DEBUG: View 2 : 0.53164556962
+2016-08-24 11:12:45,618 DEBUG: View 3 : 0.5
+2016-08-24 11:12:45,681 DEBUG: Best view : Methyl_
+2016-08-24 11:12:46,144 DEBUG: Start: Iteration 8
+2016-08-24 11:12:46,161 DEBUG: View 0 : 0.449367088608
+2016-08-24 11:12:46,169 DEBUG: View 1 : 0.436708860759
+2016-08-24 11:12:46,205 DEBUG: View 2 : 0.525316455696
+2016-08-24 11:12:46,213 DEBUG: View 3 : 0.506329113924
+2016-08-24 11:12:46,277 DEBUG: Best view : RANSeq_
+2016-08-24 11:12:46,809 DEBUG: Start: Iteration 9
+2016-08-24 11:12:46,825 DEBUG: View 0 : 0.487341772152
+2016-08-24 11:12:46,833 DEBUG: View 1 : 0.658227848101
+2016-08-24 11:12:46,870 DEBUG: View 2 : 0.462025316456
+2016-08-24 11:12:46,877 DEBUG: View 3 : 0.481012658228
+2016-08-24 11:12:46,944 DEBUG: Best view : MiRNA__
+2016-08-24 11:12:47,535 DEBUG: Start: Iteration 10
+2016-08-24 11:12:47,552 DEBUG: View 0 : 0.474683544304
+2016-08-24 11:12:47,560 DEBUG: View 1 : 0.588607594937
+2016-08-24 11:12:47,596 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:12:47,604 DEBUG: View 3 : 0.525316455696
+2016-08-24 11:12:47,673 DEBUG: Best view : MiRNA__
+2016-08-24 11:12:48,319 DEBUG: Start: Iteration 11
+2016-08-24 11:12:48,336 DEBUG: View 0 : 0.46835443038
+2016-08-24 11:12:48,344 DEBUG: View 1 : 0.639240506329
+2016-08-24 11:12:48,380 DEBUG: View 2 : 0.537974683544
+2016-08-24 11:12:48,388 DEBUG: View 3 : 0.53164556962
+2016-08-24 11:12:48,460 DEBUG: Best view : MiRNA__
+2016-08-24 11:12:49,176 DEBUG: Start: Iteration 12
+2016-08-24 11:12:49,193 DEBUG: View 0 : 0.411392405063
+2016-08-24 11:12:49,201 DEBUG: View 1 : 0.626582278481
+2016-08-24 11:12:49,239 DEBUG: View 2 : 0.379746835443
+2016-08-24 11:12:49,247 DEBUG: View 3 : 0.607594936709
+2016-08-24 11:12:49,323 DEBUG: Best view : MiRNA__
+2016-08-24 11:12:50,095 DEBUG: Start: Iteration 13
+2016-08-24 11:12:50,112 DEBUG: View 0 : 0.46835443038
+2016-08-24 11:12:50,120 DEBUG: View 1 : 0.405063291139
+2016-08-24 11:12:50,157 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:12:50,165 DEBUG: View 3 : 0.582278481013
+2016-08-24 11:12:50,241 DEBUG: Best view : Clinic_
+2016-08-24 11:12:51,101 DEBUG: Start: Iteration 14
+2016-08-24 11:12:51,117 DEBUG: View 0 : 0.569620253165
+2016-08-24 11:12:51,125 DEBUG: View 1 : 0.594936708861
+2016-08-24 11:12:51,162 DEBUG: View 2 : 0.424050632911
+2016-08-24 11:12:51,170 DEBUG: View 3 : 0.392405063291
+2016-08-24 11:12:51,248 DEBUG: Best view : MiRNA__
+2016-08-24 11:12:52,146 DEBUG: Start: Iteration 15
+2016-08-24 11:12:52,163 DEBUG: View 0 : 0.594936708861
+2016-08-24 11:12:52,171 DEBUG: View 1 : 0.651898734177
+2016-08-24 11:12:52,208 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:12:52,215 DEBUG: View 3 : 0.5
+2016-08-24 11:12:52,297 DEBUG: Best view : MiRNA__
+2016-08-24 11:12:53,236 DEBUG: Start: Iteration 16
+2016-08-24 11:12:53,252 DEBUG: View 0 : 0.386075949367
+2016-08-24 11:12:53,260 DEBUG: View 1 : 0.518987341772
+2016-08-24 11:12:53,297 DEBUG: View 2 : 0.588607594937
+2016-08-24 11:12:53,305 DEBUG: View 3 : 0.53164556962
+2016-08-24 11:12:53,388 DEBUG: Best view : RANSeq_
+2016-08-24 11:12:54,407 DEBUG: Start: Iteration 17
+2016-08-24 11:12:54,424 DEBUG: View 0 : 0.626582278481
+2016-08-24 11:12:54,432 DEBUG: View 1 : 0.550632911392
+2016-08-24 11:12:54,469 DEBUG: View 2 : 0.5
+2016-08-24 11:12:54,476 DEBUG: View 3 : 0.373417721519
+2016-08-24 11:12:54,562 DEBUG: Best view : Methyl_
+2016-08-24 11:12:55,640 DEBUG: Start: Iteration 18
+2016-08-24 11:12:55,657 DEBUG: View 0 : 0.424050632911
+2016-08-24 11:12:55,665 DEBUG: View 1 : 0.398734177215
+2016-08-24 11:12:55,701 DEBUG: View 2 : 0.658227848101
+2016-08-24 11:12:55,709 DEBUG: View 3 : 0.525316455696
+2016-08-24 11:12:55,796 DEBUG: Best view : RANSeq_
+2016-08-24 11:12:56,943 DEBUG: Start: Iteration 19
+2016-08-24 11:12:56,960 DEBUG: View 0 : 0.556962025316
+2016-08-24 11:12:56,968 DEBUG: View 1 : 0.392405063291
+2016-08-24 11:12:57,005 DEBUG: View 2 : 0.613924050633
+2016-08-24 11:12:57,013 DEBUG: View 3 : 0.677215189873
+2016-08-24 11:12:57,105 DEBUG: Best view : Clinic_
+2016-08-24 11:12:58,305 DEBUG: Start: Iteration 20
+2016-08-24 11:12:58,322 DEBUG: View 0 : 0.417721518987
+2016-08-24 11:12:58,330 DEBUG: View 1 : 0.436708860759
+2016-08-24 11:12:58,367 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:12:58,374 DEBUG: View 3 : 0.443037974684
+2016-08-24 11:12:58,374 WARNING: WARNING: All bad for iteration 19
+2016-08-24 11:12:58,467 DEBUG: Best view : Clinic_
+2016-08-24 11:12:59,738 DEBUG: Start: Iteration 21
+2016-08-24 11:12:59,755 DEBUG: View 0 : 0.430379746835
+2016-08-24 11:12:59,763 DEBUG: View 1 : 0.506329113924
+2016-08-24 11:12:59,800 DEBUG: View 2 : 0.493670886076
+2016-08-24 11:12:59,807 DEBUG: View 3 : 0.632911392405
+2016-08-24 11:12:59,904 DEBUG: Best view : Clinic_
+2016-08-24 11:13:01,234 DEBUG: Start: Iteration 22
+2016-08-24 11:13:01,251 DEBUG: View 0 : 0.462025316456
+2016-08-24 11:13:01,259 DEBUG: View 1 : 0.506329113924
+2016-08-24 11:13:01,296 DEBUG: View 2 : 0.620253164557
+2016-08-24 11:13:01,304 DEBUG: View 3 : 0.575949367089
+2016-08-24 11:13:01,401 DEBUG: Best view : RANSeq_
+2016-08-24 11:13:02,803 DEBUG: Start: Iteration 23
+2016-08-24 11:13:02,820 DEBUG: View 0 : 0.607594936709
+2016-08-24 11:13:02,828 DEBUG: View 1 : 0.518987341772
+2016-08-24 11:13:02,866 DEBUG: View 2 : 0.436708860759
+2016-08-24 11:13:02,874 DEBUG: View 3 : 0.436708860759
+2016-08-24 11:13:02,973 DEBUG: Best view : Methyl_
+2016-08-24 11:13:04,490 DEBUG: Start: Iteration 24
+2016-08-24 11:13:04,508 DEBUG: View 0 : 0.316455696203
+2016-08-24 11:13:04,515 DEBUG: View 1 : 0.373417721519
+2016-08-24 11:13:04,552 DEBUG: View 2 : 0.588607594937
+2016-08-24 11:13:04,560 DEBUG: View 3 : 0.487341772152
+2016-08-24 11:13:04,661 DEBUG: Best view : RANSeq_
+2016-08-24 11:13:06,180 DEBUG: Start: Iteration 25
+2016-08-24 11:13:06,198 DEBUG: View 0 : 0.569620253165
+2016-08-24 11:13:06,206 DEBUG: View 1 : 0.436708860759
+2016-08-24 11:13:06,243 DEBUG: View 2 : 0.556962025316
+2016-08-24 11:13:06,250 DEBUG: View 3 : 0.392405063291
+2016-08-24 11:13:06,355 DEBUG: Best view : Methyl_
+2016-08-24 11:13:07,932 DEBUG: Start: Iteration 26
+2016-08-24 11:13:07,948 DEBUG: View 0 : 0.512658227848
+2016-08-24 11:13:07,956 DEBUG: View 1 : 0.689873417722
+2016-08-24 11:13:07,993 DEBUG: View 2 : 0.537974683544
+2016-08-24 11:13:08,001 DEBUG: View 3 : 0.417721518987
+2016-08-24 11:13:08,107 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:09,754 DEBUG: Start: Iteration 27
+2016-08-24 11:13:09,770 DEBUG: View 0 : 0.462025316456
+2016-08-24 11:13:09,778 DEBUG: View 1 : 0.588607594937
+2016-08-24 11:13:09,815 DEBUG: View 2 : 0.607594936709
+2016-08-24 11:13:09,823 DEBUG: View 3 : 0.46835443038
+2016-08-24 11:13:09,931 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:11,652 DEBUG: Start: Iteration 28
+2016-08-24 11:13:11,668 DEBUG: View 0 : 0.588607594937
+2016-08-24 11:13:11,676 DEBUG: View 1 : 0.569620253165
+2016-08-24 11:13:11,714 DEBUG: View 2 : 0.582278481013
+2016-08-24 11:13:11,722 DEBUG: View 3 : 0.537974683544
+2016-08-24 11:13:11,832 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:13,601 DEBUG: Start: Iteration 29
+2016-08-24 11:13:13,617 DEBUG: View 0 : 0.645569620253
+2016-08-24 11:13:13,625 DEBUG: View 1 : 0.5
+2016-08-24 11:13:13,663 DEBUG: View 2 : 0.556962025316
+2016-08-24 11:13:13,670 DEBUG: View 3 : 0.645569620253
+2016-08-24 11:13:13,786 DEBUG: Best view : Methyl_
+2016-08-24 11:13:15,623 DEBUG: Start: Iteration 30
+2016-08-24 11:13:15,640 DEBUG: View 0 : 0.518987341772
+2016-08-24 11:13:15,648 DEBUG: View 1 : 0.46835443038
+2016-08-24 11:13:15,685 DEBUG: View 2 : 0.506329113924
+2016-08-24 11:13:15,693 DEBUG: View 3 : 0.481012658228
+2016-08-24 11:13:15,810 DEBUG: Best view : Methyl_
+2016-08-24 11:13:17,695 DEBUG: Start: Iteration 31
+2016-08-24 11:13:17,711 DEBUG: View 0 : 0.645569620253
+2016-08-24 11:13:17,719 DEBUG: View 1 : 0.544303797468
+2016-08-24 11:13:17,755 DEBUG: View 2 : 0.493670886076
+2016-08-24 11:13:17,763 DEBUG: View 3 : 0.386075949367
+2016-08-24 11:13:17,880 DEBUG: Best view : Methyl_
+2016-08-24 11:13:19,816 DEBUG: Start: Iteration 32
+2016-08-24 11:13:19,832 DEBUG: View 0 : 0.436708860759
+2016-08-24 11:13:19,840 DEBUG: View 1 : 0.430379746835
+2016-08-24 11:13:19,877 DEBUG: View 2 : 0.569620253165
+2016-08-24 11:13:19,885 DEBUG: View 3 : 0.563291139241
+2016-08-24 11:13:20,004 DEBUG: Best view : Clinic_
+2016-08-24 11:13:21,998 DEBUG: Start: Iteration 33
+2016-08-24 11:13:22,015 DEBUG: View 0 : 0.487341772152
+2016-08-24 11:13:22,023 DEBUG: View 1 : 0.417721518987
+2016-08-24 11:13:22,060 DEBUG: View 2 : 0.506329113924
+2016-08-24 11:13:22,067 DEBUG: View 3 : 0.556962025316
+2016-08-24 11:13:22,189 DEBUG: Best view : Clinic_
+2016-08-24 11:13:24,238 DEBUG: Start: Iteration 34
+2016-08-24 11:13:24,255 DEBUG: View 0 : 0.582278481013
+2016-08-24 11:13:24,263 DEBUG: View 1 : 0.348101265823
+2016-08-24 11:13:24,299 DEBUG: View 2 : 0.462025316456
+2016-08-24 11:13:24,307 DEBUG: View 3 : 0.525316455696
+2016-08-24 11:13:24,431 DEBUG: Best view : Methyl_
+2016-08-24 11:13:26,552 DEBUG: Start: Iteration 35
+2016-08-24 11:13:26,568 DEBUG: View 0 : 0.367088607595
+2016-08-24 11:13:26,576 DEBUG: View 1 : 0.588607594937
+2016-08-24 11:13:26,613 DEBUG: View 2 : 0.398734177215
+2016-08-24 11:13:26,621 DEBUG: View 3 : 0.563291139241
+2016-08-24 11:13:26,747 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:28,935 DEBUG: Start: Iteration 36
+2016-08-24 11:13:28,952 DEBUG: View 0 : 0.575949367089
+2016-08-24 11:13:28,960 DEBUG: View 1 : 0.518987341772
+2016-08-24 11:13:28,997 DEBUG: View 2 : 0.537974683544
+2016-08-24 11:13:29,004 DEBUG: View 3 : 0.46835443038
+2016-08-24 11:13:29,132 DEBUG: Best view : Methyl_
+2016-08-24 11:13:31,405 DEBUG: Start: Iteration 37
+2016-08-24 11:13:31,423 DEBUG: View 0 : 0.569620253165
+2016-08-24 11:13:31,431 DEBUG: View 1 : 0.556962025316
+2016-08-24 11:13:31,468 DEBUG: View 2 : 0.424050632911
+2016-08-24 11:13:31,476 DEBUG: View 3 : 0.563291139241
+2016-08-24 11:13:31,606 DEBUG: Best view : Methyl_
+2016-08-24 11:13:33,902 DEBUG: Start: Iteration 38
+2016-08-24 11:13:33,919 DEBUG: View 0 : 0.601265822785
+2016-08-24 11:13:33,927 DEBUG: View 1 : 0.367088607595
+2016-08-24 11:13:33,963 DEBUG: View 2 : 0.392405063291
+2016-08-24 11:13:33,971 DEBUG: View 3 : 0.639240506329
+2016-08-24 11:13:34,104 DEBUG: Best view : Clinic_
+2016-08-24 11:13:36,607 DEBUG: Start: Iteration 39
+2016-08-24 11:13:36,624 DEBUG: View 0 : 0.360759493671
+2016-08-24 11:13:36,631 DEBUG: View 1 : 0.405063291139
+2016-08-24 11:13:36,668 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:13:36,676 DEBUG: View 3 : 0.575949367089
+2016-08-24 11:13:36,811 DEBUG: Best view : Clinic_
+2016-08-24 11:13:39,566 DEBUG: Start: Iteration 40
+2016-08-24 11:13:39,594 DEBUG: View 0 : 0.550632911392
+2016-08-24 11:13:39,608 DEBUG: View 1 : 0.449367088608
+2016-08-24 11:13:39,662 DEBUG: View 2 : 0.474683544304
+2016-08-24 11:13:39,675 DEBUG: View 3 : 0.493670886076
+2016-08-24 11:13:39,892 DEBUG: Best view : Methyl_
+2016-08-24 11:13:42,508 DEBUG: Start: Iteration 41
+2016-08-24 11:13:42,525 DEBUG: View 0 : 0.46835443038
+2016-08-24 11:13:42,533 DEBUG: View 1 : 0.506329113924
+2016-08-24 11:13:42,570 DEBUG: View 2 : 0.506329113924
+2016-08-24 11:13:42,578 DEBUG: View 3 : 0.53164556962
+2016-08-24 11:13:42,720 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:45,271 DEBUG: Start: Iteration 42
+2016-08-24 11:13:45,289 DEBUG: View 0 : 0.53164556962
+2016-08-24 11:13:45,297 DEBUG: View 1 : 0.670886075949
+2016-08-24 11:13:45,334 DEBUG: View 2 : 0.537974683544
+2016-08-24 11:13:45,342 DEBUG: View 3 : 0.436708860759
+2016-08-24 11:13:45,484 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:48,085 DEBUG: Start: Iteration 43
+2016-08-24 11:13:48,102 DEBUG: View 0 : 0.443037974684
+2016-08-24 11:13:48,110 DEBUG: View 1 : 0.607594936709
+2016-08-24 11:13:48,147 DEBUG: View 2 : 0.487341772152
+2016-08-24 11:13:48,155 DEBUG: View 3 : 0.424050632911
+2016-08-24 11:13:48,299 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:50,954 DEBUG: Start: Iteration 44
+2016-08-24 11:13:50,970 DEBUG: View 0 : 0.443037974684
+2016-08-24 11:13:50,978 DEBUG: View 1 : 0.537974683544
+2016-08-24 11:13:51,016 DEBUG: View 2 : 0.481012658228
+2016-08-24 11:13:51,024 DEBUG: View 3 : 0.537974683544
+2016-08-24 11:13:51,170 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:53,901 DEBUG: Start: Iteration 45
+2016-08-24 11:13:53,918 DEBUG: View 0 : 0.474683544304
+2016-08-24 11:13:53,926 DEBUG: View 1 : 0.664556962025
+2016-08-24 11:13:53,963 DEBUG: View 2 : 0.443037974684
+2016-08-24 11:13:53,971 DEBUG: View 3 : 0.632911392405
+2016-08-24 11:13:54,120 DEBUG: Best view : MiRNA__
+2016-08-24 11:13:57,012 DEBUG: Start: Iteration 46
+2016-08-24 11:13:57,030 DEBUG: View 0 : 0.411392405063
+2016-08-24 11:13:57,038 DEBUG: View 1 : 0.727848101266
+2016-08-24 11:13:57,077 DEBUG: View 2 : 0.436708860759
+2016-08-24 11:13:57,085 DEBUG: View 3 : 0.474683544304
+2016-08-24 11:13:57,239 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:00,114 DEBUG: Start: Iteration 47
+2016-08-24 11:14:00,131 DEBUG: View 0 : 0.487341772152
+2016-08-24 11:14:00,138 DEBUG: View 1 : 0.607594936709
+2016-08-24 11:14:00,175 DEBUG: View 2 : 0.449367088608
+2016-08-24 11:14:00,183 DEBUG: View 3 : 0.525316455696
+2016-08-24 11:14:00,338 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:03,280 DEBUG: Start: Iteration 48
+2016-08-24 11:14:03,297 DEBUG: View 0 : 0.544303797468
+2016-08-24 11:14:03,304 DEBUG: View 1 : 0.613924050633
+2016-08-24 11:14:03,341 DEBUG: View 2 : 0.518987341772
+2016-08-24 11:14:03,349 DEBUG: View 3 : 0.436708860759
+2016-08-24 11:14:03,509 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:06,498 DEBUG: Start: Iteration 49
+2016-08-24 11:14:06,514 DEBUG: View 0 : 0.392405063291
+2016-08-24 11:14:06,522 DEBUG: View 1 : 0.721518987342
+2016-08-24 11:14:06,559 DEBUG: View 2 : 0.405063291139
+2016-08-24 11:14:06,567 DEBUG: View 3 : 0.518987341772
+2016-08-24 11:14:06,728 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:09,769 DEBUG: Start: Iteration 50
+2016-08-24 11:14:09,789 DEBUG: View 0 : 0.462025316456
+2016-08-24 11:14:09,797 DEBUG: View 1 : 0.53164556962
+2016-08-24 11:14:09,839 DEBUG: View 2 : 0.53164556962
+2016-08-24 11:14:09,848 DEBUG: View 3 : 0.525316455696
+2016-08-24 11:14:10,022 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:13,136 DEBUG: Start: Iteration 51
+2016-08-24 11:14:13,152 DEBUG: View 0 : 0.582278481013
+2016-08-24 11:14:13,160 DEBUG: View 1 : 0.46835443038
+2016-08-24 11:14:13,197 DEBUG: View 2 : 0.563291139241
+2016-08-24 11:14:13,205 DEBUG: View 3 : 0.518987341772
+2016-08-24 11:14:13,366 DEBUG: Best view : Methyl_
+2016-08-24 11:14:16,488 DEBUG: Start: Iteration 52
+2016-08-24 11:14:16,505 DEBUG: View 0 : 0.373417721519
+2016-08-24 11:14:16,513 DEBUG: View 1 : 0.518987341772
+2016-08-24 11:14:16,550 DEBUG: View 2 : 0.386075949367
+2016-08-24 11:14:16,558 DEBUG: View 3 : 0.487341772152
+2016-08-24 11:14:16,722 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:19,893 DEBUG: Start: Iteration 53
+2016-08-24 11:14:19,910 DEBUG: View 0 : 0.563291139241
+2016-08-24 11:14:19,917 DEBUG: View 1 : 0.53164556962
+2016-08-24 11:14:19,954 DEBUG: View 2 : 0.537974683544
+2016-08-24 11:14:19,961 DEBUG: View 3 : 0.550632911392
+2016-08-24 11:14:20,128 DEBUG: Best view : Methyl_
+2016-08-24 11:14:23,363 DEBUG: Start: Iteration 54
+2016-08-24 11:14:23,380 DEBUG: View 0 : 0.613924050633
+2016-08-24 11:14:23,388 DEBUG: View 1 : 0.455696202532
+2016-08-24 11:14:23,425 DEBUG: View 2 : 0.601265822785
+2016-08-24 11:14:23,433 DEBUG: View 3 : 0.436708860759
+2016-08-24 11:14:23,601 DEBUG: Best view : Methyl_
+2016-08-24 11:14:26,896 DEBUG: Start: Iteration 55
+2016-08-24 11:14:26,913 DEBUG: View 0 : 0.493670886076
+2016-08-24 11:14:26,921 DEBUG: View 1 : 0.626582278481
+2016-08-24 11:14:26,958 DEBUG: View 2 : 0.455696202532
+2016-08-24 11:14:26,965 DEBUG: View 3 : 0.398734177215
+2016-08-24 11:14:27,137 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:30,496 DEBUG: Start: Iteration 56
+2016-08-24 11:14:30,513 DEBUG: View 0 : 0.550632911392
+2016-08-24 11:14:30,521 DEBUG: View 1 : 0.664556962025
+2016-08-24 11:14:30,558 DEBUG: View 2 : 0.588607594937
+2016-08-24 11:14:30,565 DEBUG: View 3 : 0.645569620253
+2016-08-24 11:14:30,739 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:34,390 DEBUG: Start: Iteration 57
+2016-08-24 11:14:34,414 DEBUG: View 0 : 0.506329113924
+2016-08-24 11:14:34,422 DEBUG: View 1 : 0.512658227848
+2016-08-24 11:14:34,460 DEBUG: View 2 : 0.46835443038
+2016-08-24 11:14:34,468 DEBUG: View 3 : 0.569620253165
+2016-08-24 11:14:34,648 DEBUG: Best view : Clinic_
+2016-08-24 11:14:38,374 DEBUG: Start: Iteration 58
+2016-08-24 11:14:38,391 DEBUG: View 0 : 0.639240506329
+2016-08-24 11:14:38,399 DEBUG: View 1 : 0.651898734177
+2016-08-24 11:14:38,436 DEBUG: View 2 : 0.398734177215
+2016-08-24 11:14:38,444 DEBUG: View 3 : 0.556962025316
+2016-08-24 11:14:38,627 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:42,400 DEBUG: Start: Iteration 59
+2016-08-24 11:14:42,419 DEBUG: View 0 : 0.620253164557
+2016-08-24 11:14:42,428 DEBUG: View 1 : 0.677215189873
+2016-08-24 11:14:42,471 DEBUG: View 2 : 0.411392405063
+2016-08-24 11:14:42,480 DEBUG: View 3 : 0.512658227848
+2016-08-24 11:14:42,689 DEBUG: Best view : MiRNA__
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111445-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111445-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..52ce30c5ad85ac008cf378c0daf65475f8d8d800
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-111445-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,15314 @@
+2016-08-24 11:14:45,495 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 11:14:45,495 INFO: Info: Labels used: No, Yes
+2016-08-24 11:14:45,496 INFO: Info: Length of dataset:347
+2016-08-24 11:14:45,497 INFO: ### Main Programm for Multiview Classification
+2016-08-24 11:14:45,498 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 11:14:45,498 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 11:14:45,499 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 11:14:45,499 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 11:14:45,500 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 11:14:45,500 INFO: Done: Read Database Files
+2016-08-24 11:14:45,500 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 11:14:45,506 INFO: Done: Determine validation split
+2016-08-24 11:14:45,506 INFO: Start: Determine 2 folds
+2016-08-24 11:14:45,517 INFO: Info: Length of Learning Sets: 122
+2016-08-24 11:14:45,517 INFO: Info: Length of Testing Sets: 122
+2016-08-24 11:14:45,517 INFO: Info: Length of Validation Set: 103
+2016-08-24 11:14:45,517 INFO: Done: Determine folds
+2016-08-24 11:14:45,518 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 11:14:45,518 INFO: Start: Fold number 1
+2016-08-24 11:14:47,122 DEBUG: Start: Iteration 1
+2016-08-24 11:14:47,138 DEBUG: View 0 : 0.372670807453
+2016-08-24 11:14:47,146 DEBUG: View 1 : 0.627329192547
+2016-08-24 11:14:47,177 DEBUG: View 2 : 0.372670807453
+2016-08-24 11:14:47,185 DEBUG: View 3 : 0.627329192547
+2016-08-24 11:14:47,227 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:47,301 DEBUG: Start: Iteration 2
+2016-08-24 11:14:47,320 DEBUG: View 0 : 0.608695652174
+2016-08-24 11:14:47,328 DEBUG: View 1 : 0.726708074534
+2016-08-24 11:14:47,423 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:14:47,432 DEBUG: View 3 : 0.683229813665
+2016-08-24 11:14:47,478 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:47,611 DEBUG: Start: Iteration 3
+2016-08-24 11:14:47,629 DEBUG: View 0 : 0.552795031056
+2016-08-24 11:14:47,637 DEBUG: View 1 : 0.645962732919
+2016-08-24 11:14:47,759 DEBUG: View 2 : 0.534161490683
+2016-08-24 11:14:47,771 DEBUG: View 3 : 0.633540372671
+2016-08-24 11:14:47,849 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:48,046 DEBUG: Start: Iteration 4
+2016-08-24 11:14:48,064 DEBUG: View 0 : 0.577639751553
+2016-08-24 11:14:48,072 DEBUG: View 1 : 0.391304347826
+2016-08-24 11:14:48,164 DEBUG: View 2 : 0.527950310559
+2016-08-24 11:14:48,172 DEBUG: View 3 : 0.55900621118
+2016-08-24 11:14:48,228 DEBUG: Best view : RANSeq_
+2016-08-24 11:14:48,495 DEBUG: Start: Iteration 5
+2016-08-24 11:14:48,513 DEBUG: View 0 : 0.453416149068
+2016-08-24 11:14:48,521 DEBUG: View 1 : 0.689440993789
+2016-08-24 11:14:48,604 DEBUG: View 2 : 0.484472049689
+2016-08-24 11:14:48,612 DEBUG: View 3 : 0.577639751553
+2016-08-24 11:14:48,670 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:48,996 DEBUG: Start: Iteration 6
+2016-08-24 11:14:49,014 DEBUG: View 0 : 0.596273291925
+2016-08-24 11:14:49,021 DEBUG: View 1 : 0.645962732919
+2016-08-24 11:14:49,113 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:14:49,121 DEBUG: View 3 : 0.608695652174
+2016-08-24 11:14:49,182 DEBUG: Best view : Clinic_
+2016-08-24 11:14:49,566 DEBUG: Start: Iteration 7
+2016-08-24 11:14:49,584 DEBUG: View 0 : 0.509316770186
+2016-08-24 11:14:49,592 DEBUG: View 1 : 0.72049689441
+2016-08-24 11:14:49,679 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:14:49,687 DEBUG: View 3 : 0.546583850932
+2016-08-24 11:14:49,750 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:50,217 DEBUG: Start: Iteration 8
+2016-08-24 11:14:50,235 DEBUG: View 0 : 0.540372670807
+2016-08-24 11:14:50,243 DEBUG: View 1 : 0.639751552795
+2016-08-24 11:14:50,331 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:14:50,339 DEBUG: View 3 : 0.621118012422
+2016-08-24 11:14:50,404 DEBUG: Best view : Clinic_
+2016-08-24 11:14:50,908 DEBUG: Start: Iteration 9
+2016-08-24 11:14:50,926 DEBUG: View 0 : 0.614906832298
+2016-08-24 11:14:50,934 DEBUG: View 1 : 0.571428571429
+2016-08-24 11:14:51,028 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:14:51,036 DEBUG: View 3 : 0.565217391304
+2016-08-24 11:14:51,104 DEBUG: Best view : Clinic_
+2016-08-24 11:14:51,669 DEBUG: Start: Iteration 10
+2016-08-24 11:14:51,687 DEBUG: View 0 : 0.608695652174
+2016-08-24 11:14:51,695 DEBUG: View 1 : 0.689440993789
+2016-08-24 11:14:51,787 DEBUG: View 2 : 0.540372670807
+2016-08-24 11:14:51,795 DEBUG: View 3 : 0.639751552795
+2016-08-24 11:14:51,865 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:52,493 DEBUG: Start: Iteration 11
+2016-08-24 11:14:52,511 DEBUG: View 0 : 0.596273291925
+2016-08-24 11:14:52,519 DEBUG: View 1 : 0.465838509317
+2016-08-24 11:14:52,606 DEBUG: View 2 : 0.565217391304
+2016-08-24 11:14:52,614 DEBUG: View 3 : 0.490683229814
+2016-08-24 11:14:52,687 DEBUG: Best view : RANSeq_
+2016-08-24 11:14:53,382 DEBUG: Start: Iteration 12
+2016-08-24 11:14:53,401 DEBUG: View 0 : 0.378881987578
+2016-08-24 11:14:53,409 DEBUG: View 1 : 0.614906832298
+2016-08-24 11:14:53,498 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:14:53,506 DEBUG: View 3 : 0.633540372671
+2016-08-24 11:14:53,580 DEBUG: Best view : Clinic_
+2016-08-24 11:14:54,336 DEBUG: Start: Iteration 13
+2016-08-24 11:14:54,354 DEBUG: View 0 : 0.689440993789
+2016-08-24 11:14:54,362 DEBUG: View 1 : 0.577639751553
+2016-08-24 11:14:54,450 DEBUG: View 2 : 0.596273291925
+2016-08-24 11:14:54,458 DEBUG: View 3 : 0.683229813665
+2016-08-24 11:14:54,535 DEBUG: Best view : Clinic_
+2016-08-24 11:14:55,380 DEBUG: Start: Iteration 14
+2016-08-24 11:14:55,399 DEBUG: View 0 : 0.459627329193
+2016-08-24 11:14:55,408 DEBUG: View 1 : 0.546583850932
+2016-08-24 11:14:55,511 DEBUG: View 2 : 0.608695652174
+2016-08-24 11:14:55,520 DEBUG: View 3 : 0.621118012422
+2016-08-24 11:14:55,597 DEBUG: Best view : Clinic_
+2016-08-24 11:14:56,463 DEBUG: Start: Iteration 15
+2016-08-24 11:14:56,480 DEBUG: View 0 : 0.515527950311
+2016-08-24 11:14:56,488 DEBUG: View 1 : 0.633540372671
+2016-08-24 11:14:56,580 DEBUG: View 2 : 0.527950310559
+2016-08-24 11:14:56,588 DEBUG: View 3 : 0.484472049689
+2016-08-24 11:14:56,668 DEBUG: Best view : MiRNA__
+2016-08-24 11:14:57,608 DEBUG: Start: Iteration 16
+2016-08-24 11:14:57,628 DEBUG: View 0 : 0.484472049689
+2016-08-24 11:14:57,637 DEBUG: View 1 : 0.596273291925
+2016-08-24 11:14:57,734 DEBUG: View 2 : 0.608695652174
+2016-08-24 11:14:57,742 DEBUG: View 3 : 0.627329192547
+2016-08-24 11:14:57,824 DEBUG: Best view : Clinic_
+2016-08-24 11:14:58,815 DEBUG: Start: Iteration 17
+2016-08-24 11:14:58,833 DEBUG: View 0 : 0.459627329193
+2016-08-24 11:14:58,841 DEBUG: View 1 : 0.67701863354
+2016-08-24 11:14:58,934 DEBUG: View 2 : 0.621118012422
+2016-08-24 11:14:58,942 DEBUG: View 3 : 0.590062111801
+2016-08-24 11:14:59,028 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:00,093 DEBUG: Start: Iteration 18
+2016-08-24 11:15:00,112 DEBUG: View 0 : 0.67701863354
+2016-08-24 11:15:00,120 DEBUG: View 1 : 0.608695652174
+2016-08-24 11:15:00,210 DEBUG: View 2 : 0.515527950311
+2016-08-24 11:15:00,217 DEBUG: View 3 : 0.708074534161
+2016-08-24 11:15:00,304 DEBUG: Best view : Clinic_
+2016-08-24 11:15:01,416 DEBUG: Start: Iteration 19
+2016-08-24 11:15:01,434 DEBUG: View 0 : 0.546583850932
+2016-08-24 11:15:01,442 DEBUG: View 1 : 0.701863354037
+2016-08-24 11:15:01,534 DEBUG: View 2 : 0.590062111801
+2016-08-24 11:15:01,542 DEBUG: View 3 : 0.639751552795
+2016-08-24 11:15:01,631 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:02,804 DEBUG: Start: Iteration 20
+2016-08-24 11:15:02,826 DEBUG: View 0 : 0.484472049689
+2016-08-24 11:15:02,834 DEBUG: View 1 : 0.490683229814
+2016-08-24 11:15:02,941 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:15:02,949 DEBUG: View 3 : 0.608695652174
+2016-08-24 11:15:03,045 DEBUG: Best view : Clinic_
+2016-08-24 11:15:04,267 DEBUG: Start: Iteration 21
+2016-08-24 11:15:04,286 DEBUG: View 0 : 0.621118012422
+2016-08-24 11:15:04,294 DEBUG: View 1 : 0.521739130435
+2016-08-24 11:15:04,382 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:15:04,389 DEBUG: View 3 : 0.633540372671
+2016-08-24 11:15:04,483 DEBUG: Best view : Clinic_
+2016-08-24 11:15:05,775 DEBUG: Start: Iteration 22
+2016-08-24 11:15:05,793 DEBUG: View 0 : 0.540372670807
+2016-08-24 11:15:05,801 DEBUG: View 1 : 0.658385093168
+2016-08-24 11:15:05,889 DEBUG: View 2 : 0.608695652174
+2016-08-24 11:15:05,898 DEBUG: View 3 : 0.527950310559
+2016-08-24 11:15:05,993 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:07,339 DEBUG: Start: Iteration 23
+2016-08-24 11:15:07,357 DEBUG: View 0 : 0.571428571429
+2016-08-24 11:15:07,364 DEBUG: View 1 : 0.534161490683
+2016-08-24 11:15:07,454 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:15:07,462 DEBUG: View 3 : 0.72049689441
+2016-08-24 11:15:07,560 DEBUG: Best view : Clinic_
+2016-08-24 11:15:08,965 DEBUG: Start: Iteration 24
+2016-08-24 11:15:08,983 DEBUG: View 0 : 0.478260869565
+2016-08-24 11:15:08,990 DEBUG: View 1 : 0.39751552795
+2016-08-24 11:15:09,083 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:15:09,091 DEBUG: View 3 : 0.614906832298
+2016-08-24 11:15:09,192 DEBUG: Best view : Clinic_
+2016-08-24 11:15:10,667 DEBUG: Start: Iteration 25
+2016-08-24 11:15:10,685 DEBUG: View 0 : 0.621118012422
+2016-08-24 11:15:10,692 DEBUG: View 1 : 0.385093167702
+2016-08-24 11:15:10,784 DEBUG: View 2 : 0.565217391304
+2016-08-24 11:15:10,791 DEBUG: View 3 : 0.552795031056
+2016-08-24 11:15:10,893 DEBUG: Best view : Methyl_
+2016-08-24 11:15:12,414 DEBUG: Start: Iteration 26
+2016-08-24 11:15:12,433 DEBUG: View 0 : 0.633540372671
+2016-08-24 11:15:12,440 DEBUG: View 1 : 0.577639751553
+2016-08-24 11:15:12,533 DEBUG: View 2 : 0.527950310559
+2016-08-24 11:15:12,541 DEBUG: View 3 : 0.67701863354
+2016-08-24 11:15:12,652 DEBUG: Best view : Clinic_
+2016-08-24 11:15:14,242 DEBUG: Start: Iteration 27
+2016-08-24 11:15:14,260 DEBUG: View 0 : 0.55900621118
+2016-08-24 11:15:14,268 DEBUG: View 1 : 0.614906832298
+2016-08-24 11:15:14,363 DEBUG: View 2 : 0.546583850932
+2016-08-24 11:15:14,371 DEBUG: View 3 : 0.546583850932
+2016-08-24 11:15:14,477 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:16,122 DEBUG: Start: Iteration 28
+2016-08-24 11:15:16,140 DEBUG: View 0 : 0.583850931677
+2016-08-24 11:15:16,148 DEBUG: View 1 : 0.645962732919
+2016-08-24 11:15:16,243 DEBUG: View 2 : 0.565217391304
+2016-08-24 11:15:16,251 DEBUG: View 3 : 0.571428571429
+2016-08-24 11:15:16,360 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:18,074 DEBUG: Start: Iteration 29
+2016-08-24 11:15:18,092 DEBUG: View 0 : 0.608695652174
+2016-08-24 11:15:18,100 DEBUG: View 1 : 0.627329192547
+2016-08-24 11:15:18,193 DEBUG: View 2 : 0.521739130435
+2016-08-24 11:15:18,201 DEBUG: View 3 : 0.664596273292
+2016-08-24 11:15:18,311 DEBUG: Best view : Clinic_
+2016-08-24 11:15:20,068 DEBUG: Start: Iteration 30
+2016-08-24 11:15:20,087 DEBUG: View 0 : 0.540372670807
+2016-08-24 11:15:20,095 DEBUG: View 1 : 0.639751552795
+2016-08-24 11:15:20,193 DEBUG: View 2 : 0.552795031056
+2016-08-24 11:15:20,201 DEBUG: View 3 : 0.627329192547
+2016-08-24 11:15:20,319 DEBUG: Best view : Clinic_
+2016-08-24 11:15:22,144 DEBUG: Start: Iteration 31
+2016-08-24 11:15:22,161 DEBUG: View 0 : 0.490683229814
+2016-08-24 11:15:22,169 DEBUG: View 1 : 0.360248447205
+2016-08-24 11:15:22,259 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:15:22,267 DEBUG: View 3 : 0.534161490683
+2016-08-24 11:15:22,383 DEBUG: Best view : RANSeq_
+2016-08-24 11:15:24,278 DEBUG: Start: Iteration 32
+2016-08-24 11:15:24,297 DEBUG: View 0 : 0.534161490683
+2016-08-24 11:15:24,305 DEBUG: View 1 : 0.627329192547
+2016-08-24 11:15:24,397 DEBUG: View 2 : 0.639751552795
+2016-08-24 11:15:24,405 DEBUG: View 3 : 0.60248447205
+2016-08-24 11:15:24,524 DEBUG: Best view : RANSeq_
+2016-08-24 11:15:26,504 DEBUG: Start: Iteration 33
+2016-08-24 11:15:26,522 DEBUG: View 0 : 0.472049689441
+2016-08-24 11:15:26,529 DEBUG: View 1 : 0.639751552795
+2016-08-24 11:15:26,621 DEBUG: View 2 : 0.503105590062
+2016-08-24 11:15:26,629 DEBUG: View 3 : 0.664596273292
+2016-08-24 11:15:26,748 DEBUG: Best view : Clinic_
+2016-08-24 11:15:28,792 DEBUG: Start: Iteration 34
+2016-08-24 11:15:28,809 DEBUG: View 0 : 0.583850931677
+2016-08-24 11:15:28,817 DEBUG: View 1 : 0.55900621118
+2016-08-24 11:15:28,909 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:15:28,917 DEBUG: View 3 : 0.621118012422
+2016-08-24 11:15:29,040 DEBUG: Best view : Clinic_
+2016-08-24 11:15:31,128 DEBUG: Start: Iteration 35
+2016-08-24 11:15:31,146 DEBUG: View 0 : 0.490683229814
+2016-08-24 11:15:31,153 DEBUG: View 1 : 0.571428571429
+2016-08-24 11:15:31,241 DEBUG: View 2 : 0.652173913043
+2016-08-24 11:15:31,248 DEBUG: View 3 : 0.596273291925
+2016-08-24 11:15:31,372 DEBUG: Best view : RANSeq_
+2016-08-24 11:15:33,543 DEBUG: Start: Iteration 36
+2016-08-24 11:15:33,561 DEBUG: View 0 : 0.614906832298
+2016-08-24 11:15:33,568 DEBUG: View 1 : 0.614906832298
+2016-08-24 11:15:33,651 DEBUG: View 2 : 0.515527950311
+2016-08-24 11:15:33,659 DEBUG: View 3 : 0.565217391304
+2016-08-24 11:15:33,785 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:36,019 DEBUG: Start: Iteration 37
+2016-08-24 11:15:36,037 DEBUG: View 0 : 0.757763975155
+2016-08-24 11:15:36,045 DEBUG: View 1 : 0.60248447205
+2016-08-24 11:15:36,132 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:15:36,140 DEBUG: View 3 : 0.490683229814
+2016-08-24 11:15:36,269 DEBUG: Best view : Methyl_
+2016-08-24 11:15:38,554 DEBUG: Start: Iteration 38
+2016-08-24 11:15:38,572 DEBUG: View 0 : 0.552795031056
+2016-08-24 11:15:38,579 DEBUG: View 1 : 0.683229813665
+2016-08-24 11:15:38,669 DEBUG: View 2 : 0.534161490683
+2016-08-24 11:15:38,677 DEBUG: View 3 : 0.571428571429
+2016-08-24 11:15:38,808 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:41,153 DEBUG: Start: Iteration 39
+2016-08-24 11:15:41,170 DEBUG: View 0 : 0.652173913043
+2016-08-24 11:15:41,178 DEBUG: View 1 : 0.658385093168
+2016-08-24 11:15:41,265 DEBUG: View 2 : 0.658385093168
+2016-08-24 11:15:41,273 DEBUG: View 3 : 0.596273291925
+2016-08-24 11:15:41,405 DEBUG: Best view : RANSeq_
+2016-08-24 11:15:43,837 DEBUG: Start: Iteration 40
+2016-08-24 11:15:43,854 DEBUG: View 0 : 0.633540372671
+2016-08-24 11:15:43,862 DEBUG: View 1 : 0.39751552795
+2016-08-24 11:15:43,951 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:15:43,959 DEBUG: View 3 : 0.590062111801
+2016-08-24 11:15:44,094 DEBUG: Best view : Methyl_
+2016-08-24 11:15:46,579 DEBUG: Start: Iteration 41
+2016-08-24 11:15:46,597 DEBUG: View 0 : 0.552795031056
+2016-08-24 11:15:46,605 DEBUG: View 1 : 0.639751552795
+2016-08-24 11:15:46,694 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:15:46,702 DEBUG: View 3 : 0.478260869565
+2016-08-24 11:15:46,839 DEBUG: Best view : MiRNA__
+2016-08-24 11:15:49,378 DEBUG: Start: Iteration 42
+2016-08-24 11:15:49,396 DEBUG: View 0 : 0.565217391304
+2016-08-24 11:15:49,404 DEBUG: View 1 : 0.596273291925
+2016-08-24 11:15:49,491 DEBUG: View 2 : 0.608695652174
+2016-08-24 11:15:49,499 DEBUG: View 3 : 0.608695652174
+2016-08-24 11:15:49,638 DEBUG: Best view : Clinic_
+2016-08-24 11:15:52,257 DEBUG: Start: Iteration 43
+2016-08-24 11:15:52,275 DEBUG: View 0 : 0.701863354037
+2016-08-24 11:15:52,283 DEBUG: View 1 : 0.645962732919
+2016-08-24 11:15:52,377 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:15:52,385 DEBUG: View 3 : 0.608695652174
+2016-08-24 11:15:52,526 DEBUG: Best view : Methyl_
+2016-08-24 11:15:55,194 DEBUG: Start: Iteration 44
+2016-08-24 11:15:55,213 DEBUG: View 0 : 0.472049689441
+2016-08-24 11:15:55,221 DEBUG: View 1 : 0.496894409938
+2016-08-24 11:15:55,316 DEBUG: View 2 : 0.509316770186
+2016-08-24 11:15:55,324 DEBUG: View 3 : 0.552795031056
+2016-08-24 11:15:55,466 DEBUG: Best view : Clinic_
+2016-08-24 11:15:58,192 DEBUG: Start: Iteration 45
+2016-08-24 11:15:58,210 DEBUG: View 0 : 0.484472049689
+2016-08-24 11:15:58,217 DEBUG: View 1 : 0.621118012422
+2016-08-24 11:15:58,311 DEBUG: View 2 : 0.583850931677
+2016-08-24 11:15:58,318 DEBUG: View 3 : 0.583850931677
+2016-08-24 11:15:58,464 DEBUG: Best view : MiRNA__
+2016-08-24 11:16:01,240 DEBUG: Start: Iteration 46
+2016-08-24 11:16:01,258 DEBUG: View 0 : 0.60248447205
+2016-08-24 11:16:01,265 DEBUG: View 1 : 0.639751552795
+2016-08-24 11:16:01,360 DEBUG: View 2 : 0.565217391304
+2016-08-24 11:16:01,368 DEBUG: View 3 : 0.521739130435
+2016-08-24 11:16:01,516 DEBUG: Best view : MiRNA__
+2016-08-24 11:16:04,354 DEBUG: Start: Iteration 47
+2016-08-24 11:16:04,372 DEBUG: View 0 : 0.639751552795
+2016-08-24 11:16:04,380 DEBUG: View 1 : 0.633540372671
+2016-08-24 11:16:04,472 DEBUG: View 2 : 0.521739130435
+2016-08-24 11:16:04,480 DEBUG: View 3 : 0.490683229814
+2016-08-24 11:16:04,629 DEBUG: Best view : Methyl_
+2016-08-24 11:16:07,543 DEBUG: Start: Iteration 48
+2016-08-24 11:16:07,561 DEBUG: View 0 : 0.577639751553
+2016-08-24 11:16:07,569 DEBUG: View 1 : 0.633540372671
+2016-08-24 11:16:07,661 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:16:07,669 DEBUG: View 3 : 0.596273291925
+2016-08-24 11:16:07,822 DEBUG: Best view : Clinic_
+2016-08-24 11:16:10,789 DEBUG: Start: Iteration 49
+2016-08-24 11:16:10,807 DEBUG: View 0 : 0.453416149068
+2016-08-24 11:16:10,814 DEBUG: View 1 : 0.571428571429
+2016-08-24 11:16:10,907 DEBUG: View 2 : 0.639751552795
+2016-08-24 11:16:10,915 DEBUG: View 3 : 0.633540372671
+2016-08-24 11:16:11,069 DEBUG: Best view : Clinic_
+2016-08-24 11:16:14,095 DEBUG: Start: Iteration 50
+2016-08-24 11:16:14,112 DEBUG: View 0 : 0.670807453416
+2016-08-24 11:16:14,120 DEBUG: View 1 : 0.664596273292
+2016-08-24 11:16:14,200 DEBUG: View 2 : 0.596273291925
+2016-08-24 11:16:14,208 DEBUG: View 3 : 0.60248447205
+2016-08-24 11:16:14,365 DEBUG: Best view : Methyl_
+2016-08-24 11:16:17,472 DEBUG: Start: Iteration 51
+2016-08-24 11:16:17,490 DEBUG: View 0 : 0.652173913043
+2016-08-24 11:16:17,498 DEBUG: View 1 : 0.416149068323
+2016-08-24 11:16:17,602 DEBUG: View 2 : 0.484472049689
+2016-08-24 11:16:17,610 DEBUG: View 3 : 0.621118012422
+2016-08-24 11:16:17,772 DEBUG: Best view : Methyl_
+2016-08-24 11:16:20,914 DEBUG: Start: Iteration 52
+2016-08-24 11:16:20,932 DEBUG: View 0 : 0.689440993789
+2016-08-24 11:16:20,940 DEBUG: View 1 : 0.627329192547
+2016-08-24 11:16:21,034 DEBUG: View 2 : 0.552795031056
+2016-08-24 11:16:21,041 DEBUG: View 3 : 0.490683229814
+2016-08-24 11:16:21,205 DEBUG: Best view : Methyl_
+2016-08-24 11:16:24,426 DEBUG: Start: Iteration 53
+2016-08-24 11:16:24,443 DEBUG: View 0 : 0.565217391304
+2016-08-24 11:16:24,451 DEBUG: View 1 : 0.658385093168
+2016-08-24 11:16:24,538 DEBUG: View 2 : 0.590062111801
+2016-08-24 11:16:24,546 DEBUG: View 3 : 0.534161490683
+2016-08-24 11:16:24,710 DEBUG: Best view : MiRNA__
+2016-08-24 11:16:27,999 DEBUG: Start: Iteration 54
+2016-08-24 11:16:28,017 DEBUG: View 0 : 0.577639751553
+2016-08-24 11:16:28,025 DEBUG: View 1 : 0.434782608696
+2016-08-24 11:16:28,116 DEBUG: View 2 : 0.552795031056
+2016-08-24 11:16:28,124 DEBUG: View 3 : 0.534161490683
+2016-08-24 11:16:28,291 DEBUG: Best view : Methyl_
+2016-08-24 11:16:31,633 DEBUG: Start: Iteration 55
+2016-08-24 11:16:31,650 DEBUG: View 0 : 0.434782608696
+2016-08-24 11:16:31,658 DEBUG: View 1 : 0.645962732919
+2016-08-24 11:16:31,746 DEBUG: View 2 : 0.577639751553
+2016-08-24 11:16:31,754 DEBUG: View 3 : 0.689440993789
+2016-08-24 11:16:31,923 DEBUG: Best view : Clinic_
+2016-08-24 11:16:35,333 DEBUG: Start: Iteration 56
+2016-08-24 11:16:35,351 DEBUG: View 0 : 0.614906832298
+2016-08-24 11:16:35,359 DEBUG: View 1 : 0.857142857143
+2016-08-24 11:16:35,449 DEBUG: View 2 : 0.546583850932
+2016-08-24 11:16:35,456 DEBUG: View 3 : 0.627329192547
+2016-08-24 11:16:35,627 DEBUG: Best view : MiRNA__
+2016-08-24 11:16:39,082 DEBUG: Start: Iteration 57
+2016-08-24 11:16:39,100 DEBUG: View 0 : 0.527950310559
+2016-08-24 11:16:39,108 DEBUG: View 1 : 0.434782608696
+2016-08-24 11:16:39,201 DEBUG: View 2 : 0.621118012422
+2016-08-24 11:16:39,209 DEBUG: View 3 : 0.590062111801
+2016-08-24 11:16:39,381 DEBUG: Best view : RANSeq_
+2016-08-24 11:16:42,922 DEBUG: Start: Iteration 58
+2016-08-24 11:16:42,940 DEBUG: View 0 : 0.540372670807
+2016-08-24 11:16:42,948 DEBUG: View 1 : 0.534161490683
+2016-08-24 11:16:43,034 DEBUG: View 2 : 0.565217391304
+2016-08-24 11:16:43,041 DEBUG: View 3 : 0.490683229814
+2016-08-24 11:16:43,217 DEBUG: Best view : RANSeq_
+2016-08-24 11:16:46,827 DEBUG: Start: Iteration 59
+2016-08-24 11:16:46,845 DEBUG: View 0 : 0.55900621118
+2016-08-24 11:16:46,853 DEBUG: View 1 : 0.639751552795
+2016-08-24 11:16:46,947 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:16:46,955 DEBUG: View 3 : 0.590062111801
+2016-08-24 11:16:47,141 DEBUG: Best view : RANSeq_
+2016-08-24 11:16:50,821 DEBUG: Start: Iteration 60
+2016-08-24 11:16:50,841 DEBUG: View 0 : 0.608695652174
+2016-08-24 11:16:50,848 DEBUG: View 1 : 0.478260869565
+2016-08-24 11:16:50,938 DEBUG: View 2 : 0.596273291925
+2016-08-24 11:16:50,947 DEBUG: View 3 : 0.55900621118
+2016-08-24 11:16:51,127 DEBUG: Best view : RANSeq_
+2016-08-24 11:16:54,882 DEBUG: Start: Iteration 61
+2016-08-24 11:16:54,900 DEBUG: View 0 : 0.403726708075
+2016-08-24 11:16:54,908 DEBUG: View 1 : 0.652173913043
+2016-08-24 11:16:54,998 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:16:55,006 DEBUG: View 3 : 0.658385093168
+2016-08-24 11:16:55,186 DEBUG: Best view : Clinic_
+2016-08-24 11:16:58,982 DEBUG: Start: Iteration 62
+2016-08-24 11:16:59,000 DEBUG: View 0 : 0.509316770186
+2016-08-24 11:16:59,008 DEBUG: View 1 : 0.72049689441
+2016-08-24 11:16:59,102 DEBUG: View 2 : 0.633540372671
+2016-08-24 11:16:59,110 DEBUG: View 3 : 0.67701863354
+2016-08-24 11:16:59,295 DEBUG: Best view : MiRNA__
+2016-08-24 11:17:03,161 DEBUG: Start: Iteration 63
+2016-08-24 11:17:03,179 DEBUG: View 0 : 0.527950310559
+2016-08-24 11:17:03,187 DEBUG: View 1 : 0.484472049689
+2016-08-24 11:17:03,278 DEBUG: View 2 : 0.596273291925
+2016-08-24 11:17:03,286 DEBUG: View 3 : 0.639751552795
+2016-08-24 11:17:03,471 DEBUG: Best view : Clinic_
+2016-08-24 11:17:07,398 DEBUG: Start: Iteration 64
+2016-08-24 11:17:07,416 DEBUG: View 0 : 0.546583850932
+2016-08-24 11:17:07,425 DEBUG: View 1 : 0.633540372671
+2016-08-24 11:17:07,518 DEBUG: View 2 : 0.633540372671
+2016-08-24 11:17:07,526 DEBUG: View 3 : 0.509316770186
+2016-08-24 11:17:07,715 DEBUG: Best view : RANSeq_
+2016-08-24 11:17:11,730 DEBUG: Start: Iteration 65
+2016-08-24 11:17:11,749 DEBUG: View 0 : 0.447204968944
+2016-08-24 11:17:11,757 DEBUG: View 1 : 0.496894409938
+2016-08-24 11:17:11,849 DEBUG: View 2 : 0.614906832298
+2016-08-24 11:17:11,857 DEBUG: View 3 : 0.503105590062
+2016-08-24 11:17:12,055 DEBUG: Best view : RANSeq_
+2016-08-24 11:17:16,117 DEBUG: Start: Iteration 66
+2016-08-24 11:17:16,135 DEBUG: View 0 : 0.534161490683
+2016-08-24 11:17:16,143 DEBUG: View 1 : 0.614906832298
+2016-08-24 11:17:16,223 DEBUG: View 2 : 0.621118012422
+2016-08-24 11:17:16,231 DEBUG: View 3 : 0.683229813665
+2016-08-24 11:17:16,425 DEBUG: Best view : Clinic_
+2016-08-24 11:17:20,587 DEBUG: Start: Iteration 67
+2016-08-24 11:17:20,604 DEBUG: View 0 : 0.428571428571
+2016-08-24 11:17:20,612 DEBUG: View 1 : 0.496894409938
+2016-08-24 11:17:20,705 DEBUG: View 2 : 0.645962732919
+2016-08-24 11:17:20,713 DEBUG: View 3 : 0.60248447205
+2016-08-24 11:17:20,908 DEBUG: Best view : RANSeq_
+2016-08-24 11:17:25,155 DEBUG: Start: Iteration 68
+2016-08-24 11:17:25,173 DEBUG: View 0 : 0.534161490683
+2016-08-24 11:17:25,181 DEBUG: View 1 : 0.664596273292
+2016-08-24 11:17:25,267 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:17:25,275 DEBUG: View 3 : 0.670807453416
+2016-08-24 11:17:25,469 DEBUG: Best view : Clinic_
+2016-08-24 11:17:29,738 DEBUG: Start: Iteration 69
+2016-08-24 11:17:29,756 DEBUG: View 0 : 0.465838509317
+2016-08-24 11:17:29,764 DEBUG: View 1 : 0.633540372671
+2016-08-24 11:17:29,858 DEBUG: View 2 : 0.652173913043
+2016-08-24 11:17:29,866 DEBUG: View 3 : 0.608695652174
+2016-08-24 11:17:30,064 DEBUG: Best view : RANSeq_
+2016-08-24 11:17:34,406 DEBUG: Start: Iteration 70
+2016-08-24 11:17:34,424 DEBUG: View 0 : 0.552795031056
+2016-08-24 11:17:34,432 DEBUG: View 1 : 0.596273291925
+2016-08-24 11:17:34,520 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:17:34,528 DEBUG: View 3 : 0.608695652174
+2016-08-24 11:17:34,727 DEBUG: Best view : Clinic_
+2016-08-24 11:17:39,117 DEBUG: Start: Iteration 71
+2016-08-24 11:17:39,135 DEBUG: View 0 : 0.565217391304
+2016-08-24 11:17:39,143 DEBUG: View 1 : 0.515527950311
+2016-08-24 11:17:39,228 DEBUG: View 2 : 0.546583850932
+2016-08-24 11:17:39,236 DEBUG: View 3 : 0.621118012422
+2016-08-24 11:17:39,489 DEBUG: Best view : Clinic_
+2016-08-24 11:17:43,962 DEBUG: Start: Iteration 72
+2016-08-24 11:17:43,980 DEBUG: View 0 : 0.621118012422
+2016-08-24 11:17:43,987 DEBUG: View 1 : 0.565217391304
+2016-08-24 11:17:44,079 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:17:44,088 DEBUG: View 3 : 0.577639751553
+2016-08-24 11:17:44,293 DEBUG: Best view : Methyl_
+2016-08-24 11:17:48,830 DEBUG: Start: Iteration 73
+2016-08-24 11:17:48,850 DEBUG: View 0 : 0.67701863354
+2016-08-24 11:17:48,860 DEBUG: View 1 : 0.540372670807
+2016-08-24 11:17:48,961 DEBUG: View 2 : 0.590062111801
+2016-08-24 11:17:48,968 DEBUG: View 3 : 0.633540372671
+2016-08-24 11:17:49,176 DEBUG: Best view : Clinic_
+2016-08-24 11:17:53,775 DEBUG: Start: Iteration 74
+2016-08-24 11:17:53,793 DEBUG: View 0 : 0.453416149068
+2016-08-24 11:17:53,800 DEBUG: View 1 : 0.652173913043
+2016-08-24 11:17:53,889 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:17:53,897 DEBUG: View 3 : 0.503105590062
+2016-08-24 11:17:54,119 DEBUG: Best view : MiRNA__
+2016-08-24 11:17:58,762 DEBUG: Start: Iteration 75
+2016-08-24 11:17:58,780 DEBUG: View 0 : 0.503105590062
+2016-08-24 11:17:58,788 DEBUG: View 1 : 0.627329192547
+2016-08-24 11:17:58,880 DEBUG: View 2 : 0.652173913043
+2016-08-24 11:17:58,888 DEBUG: View 3 : 0.670807453416
+2016-08-24 11:17:59,101 DEBUG: Best view : Clinic_
+2016-08-24 11:18:03,812 DEBUG: Start: Iteration 76
+2016-08-24 11:18:03,829 DEBUG: View 0 : 0.478260869565
+2016-08-24 11:18:03,837 DEBUG: View 1 : 0.627329192547
+2016-08-24 11:18:03,929 DEBUG: View 2 : 0.596273291925
+2016-08-24 11:18:03,937 DEBUG: View 3 : 0.521739130435
+2016-08-24 11:18:04,151 DEBUG: Best view : RANSeq_
+2016-08-24 11:18:08,927 DEBUG: Start: Iteration 77
+2016-08-24 11:18:08,945 DEBUG: View 0 : 0.509316770186
+2016-08-24 11:18:08,953 DEBUG: View 1 : 0.465838509317
+2016-08-24 11:18:09,049 DEBUG: View 2 : 0.515527950311
+2016-08-24 11:18:09,057 DEBUG: View 3 : 0.552795031056
+2016-08-24 11:18:09,272 DEBUG: Best view : Clinic_
+2016-08-24 11:18:14,096 DEBUG: Start: Iteration 78
+2016-08-24 11:18:14,114 DEBUG: View 0 : 0.496894409938
+2016-08-24 11:18:14,122 DEBUG: View 1 : 0.614906832298
+2016-08-24 11:18:14,216 DEBUG: View 2 : 0.540372670807
+2016-08-24 11:18:14,223 DEBUG: View 3 : 0.583850931677
+2016-08-24 11:18:14,442 DEBUG: Best view : MiRNA__
+2016-08-24 11:18:19,347 DEBUG: Start: Iteration 79
+2016-08-24 11:18:19,365 DEBUG: View 0 : 0.608695652174
+2016-08-24 11:18:19,373 DEBUG: View 1 : 0.726708074534
+2016-08-24 11:18:19,461 DEBUG: View 2 : 0.621118012422
+2016-08-24 11:18:19,469 DEBUG: View 3 : 0.664596273292
+2016-08-24 11:18:19,693 DEBUG: Best view : MiRNA__
+2016-08-24 11:18:24,651 DEBUG: Start: Iteration 80
+2016-08-24 11:18:24,669 DEBUG: View 0 : 0.546583850932
+2016-08-24 11:18:24,676 DEBUG: View 1 : 0.633540372671
+2016-08-24 11:18:24,765 DEBUG: View 2 : 0.503105590062
+2016-08-24 11:18:24,773 DEBUG: View 3 : 0.670807453416
+2016-08-24 11:18:24,993 DEBUG: Best view : Clinic_
+2016-08-24 11:18:30,011 DEBUG: Start: Iteration 81
+2016-08-24 11:18:30,030 DEBUG: View 0 : 0.490683229814
+2016-08-24 11:18:30,038 DEBUG: View 1 : 0.577639751553
+2016-08-24 11:18:30,128 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:18:30,137 DEBUG: View 3 : 0.596273291925
+2016-08-24 11:18:30,364 DEBUG: Best view : Clinic_
+2016-08-24 11:18:35,443 DEBUG: Start: Iteration 82
+2016-08-24 11:18:35,462 DEBUG: View 0 : 0.527950310559
+2016-08-24 11:18:35,470 DEBUG: View 1 : 0.608695652174
+2016-08-24 11:18:35,558 DEBUG: View 2 : 0.552795031056
+2016-08-24 11:18:35,567 DEBUG: View 3 : 0.652173913043
+2016-08-24 11:18:35,795 DEBUG: Best view : Clinic_
+2016-08-24 11:18:40,943 DEBUG: Start: Iteration 83
+2016-08-24 11:18:40,961 DEBUG: View 0 : 0.689440993789
+2016-08-24 11:18:40,969 DEBUG: View 1 : 0.658385093168
+2016-08-24 11:18:41,058 DEBUG: View 2 : 0.521739130435
+2016-08-24 11:18:41,066 DEBUG: View 3 : 0.645962732919
+2016-08-24 11:18:41,297 DEBUG: Best view : Methyl_
+2016-08-24 11:18:46,494 DEBUG: Start: Iteration 84
+2016-08-24 11:18:46,512 DEBUG: View 0 : 0.55900621118
+2016-08-24 11:18:46,520 DEBUG: View 1 : 0.652173913043
+2016-08-24 11:18:46,614 DEBUG: View 2 : 0.608695652174
+2016-08-24 11:18:46,622 DEBUG: View 3 : 0.546583850932
+2016-08-24 11:18:46,855 DEBUG: Best view : MiRNA__
+2016-08-24 11:18:52,119 DEBUG: Start: Iteration 85
+2016-08-24 11:18:52,137 DEBUG: View 0 : 0.515527950311
+2016-08-24 11:18:52,144 DEBUG: View 1 : 0.453416149068
+2016-08-24 11:18:52,235 DEBUG: View 2 : 0.633540372671
+2016-08-24 11:18:52,243 DEBUG: View 3 : 0.577639751553
+2016-08-24 11:18:52,479 DEBUG: Best view : RANSeq_
+2016-08-24 11:18:57,816 DEBUG: Start: Iteration 86
+2016-08-24 11:18:57,834 DEBUG: View 0 : 0.614906832298
+2016-08-24 11:18:57,842 DEBUG: View 1 : 0.608695652174
+2016-08-24 11:18:57,936 DEBUG: View 2 : 0.670807453416
+2016-08-24 11:18:57,944 DEBUG: View 3 : 0.608695652174
+2016-08-24 11:18:58,180 DEBUG: Best view : RANSeq_
+2016-08-24 11:19:03,593 DEBUG: Start: Iteration 87
+2016-08-24 11:19:03,611 DEBUG: View 0 : 0.60248447205
+2016-08-24 11:19:03,619 DEBUG: View 1 : 0.608695652174
+2016-08-24 11:19:03,713 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:19:03,721 DEBUG: View 3 : 0.521739130435
+2016-08-24 11:19:03,959 DEBUG: Best view : RANSeq_
+2016-08-24 11:19:09,435 DEBUG: Start: Iteration 88
+2016-08-24 11:19:09,453 DEBUG: View 0 : 0.664596273292
+2016-08-24 11:19:09,461 DEBUG: View 1 : 0.534161490683
+2016-08-24 11:19:09,553 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:19:09,560 DEBUG: View 3 : 0.596273291925
+2016-08-24 11:19:09,799 DEBUG: Best view : Methyl_
+2016-08-24 11:19:15,336 DEBUG: Start: Iteration 89
+2016-08-24 11:19:15,355 DEBUG: View 0 : 0.527950310559
+2016-08-24 11:19:15,363 DEBUG: View 1 : 0.515527950311
+2016-08-24 11:19:15,465 DEBUG: View 2 : 0.633540372671
+2016-08-24 11:19:15,473 DEBUG: View 3 : 0.652173913043
+2016-08-24 11:19:15,721 DEBUG: Best view : Clinic_
+2016-08-24 11:19:21,322 DEBUG: Start: Iteration 90
+2016-08-24 11:19:21,340 DEBUG: View 0 : 0.478260869565
+2016-08-24 11:19:21,348 DEBUG: View 1 : 0.670807453416
+2016-08-24 11:19:21,443 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:19:21,450 DEBUG: View 3 : 0.577639751553
+2016-08-24 11:19:21,697 DEBUG: Best view : MiRNA__
+2016-08-24 11:19:27,356 DEBUG: Start: Iteration 91
+2016-08-24 11:19:27,374 DEBUG: View 0 : 0.521739130435
+2016-08-24 11:19:27,382 DEBUG: View 1 : 0.496894409938
+2016-08-24 11:19:27,473 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:19:27,481 DEBUG: View 3 : 0.527950310559
+2016-08-24 11:19:27,732 DEBUG: Best view : RANSeq_
+2016-08-24 11:19:33,475 DEBUG: Start: Iteration 92
+2016-08-24 11:19:33,493 DEBUG: View 0 : 0.546583850932
+2016-08-24 11:19:33,501 DEBUG: View 1 : 0.55900621118
+2016-08-24 11:19:33,591 DEBUG: View 2 : 0.627329192547
+2016-08-24 11:19:33,600 DEBUG: View 3 : 0.583850931677
+2016-08-24 11:19:33,851 DEBUG: Best view : RANSeq_
+2016-08-24 11:19:39,661 DEBUG: Start: Iteration 93
+2016-08-24 11:19:39,679 DEBUG: View 0 : 0.590062111801
+2016-08-24 11:19:39,687 DEBUG: View 1 : 0.708074534161
+2016-08-24 11:19:39,775 DEBUG: View 2 : 0.521739130435
+2016-08-24 11:19:39,783 DEBUG: View 3 : 0.546583850932
+2016-08-24 11:19:40,039 DEBUG: Best view : MiRNA__
+2016-08-24 11:19:45,933 DEBUG: Start: Iteration 94
+2016-08-24 11:19:45,951 DEBUG: View 0 : 0.645962732919
+2016-08-24 11:19:45,959 DEBUG: View 1 : 0.409937888199
+2016-08-24 11:19:46,043 DEBUG: View 2 : 0.55900621118
+2016-08-24 11:19:46,051 DEBUG: View 3 : 0.639751552795
+2016-08-24 11:19:46,302 DEBUG: Best view : Clinic_
+2016-08-24 11:19:52,252 DEBUG: Start: Iteration 95
+2016-08-24 11:19:52,270 DEBUG: View 0 : 0.583850931677
+2016-08-24 11:19:52,278 DEBUG: View 1 : 0.552795031056
+2016-08-24 11:19:52,367 DEBUG: View 2 : 0.552795031056
+2016-08-24 11:19:52,375 DEBUG: View 3 : 0.596273291925
+2016-08-24 11:19:52,642 DEBUG: Best view : Clinic_
+2016-08-24 11:19:58,625 DEBUG: Start: Iteration 96
+2016-08-24 11:19:58,643 DEBUG: View 0 : 0.540372670807
+2016-08-24 11:19:58,651 DEBUG: View 1 : 0.496894409938
+2016-08-24 11:19:58,742 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:19:58,749 DEBUG: View 3 : 0.465838509317
+2016-08-24 11:19:59,007 DEBUG: Best view : RANSeq_
+2016-08-24 11:20:05,084 DEBUG: Start: Iteration 97
+2016-08-24 11:20:05,103 DEBUG: View 0 : 0.577639751553
+2016-08-24 11:20:05,111 DEBUG: View 1 : 0.683229813665
+2016-08-24 11:20:05,209 DEBUG: View 2 : 0.509316770186
+2016-08-24 11:20:05,217 DEBUG: View 3 : 0.590062111801
+2016-08-24 11:20:05,489 DEBUG: Best view : MiRNA__
+2016-08-24 11:20:11,716 DEBUG: Start: Iteration 98
+2016-08-24 11:20:11,734 DEBUG: View 0 : 0.571428571429
+2016-08-24 11:20:11,743 DEBUG: View 1 : 0.621118012422
+2016-08-24 11:20:11,834 DEBUG: View 2 : 0.621118012422
+2016-08-24 11:20:11,842 DEBUG: View 3 : 0.478260869565
+2016-08-24 11:20:12,104 DEBUG: Best view : MiRNA__
+2016-08-24 11:20:18,337 DEBUG: Start: Iteration 99
+2016-08-24 11:20:18,355 DEBUG: View 0 : 0.596273291925
+2016-08-24 11:20:18,363 DEBUG: View 1 : 0.621118012422
+2016-08-24 11:20:18,460 DEBUG: View 2 : 0.571428571429
+2016-08-24 11:20:18,468 DEBUG: View 3 : 0.55900621118
+2016-08-24 11:20:18,734 DEBUG: Best view : MiRNA__
+2016-08-24 11:20:25,017 DEBUG: Start: Iteration 100
+2016-08-24 11:20:25,036 DEBUG: View 0 : 0.403726708075
+2016-08-24 11:20:25,044 DEBUG: View 1 : 0.590062111801
+2016-08-24 11:20:25,138 DEBUG: View 2 : 0.60248447205
+2016-08-24 11:20:25,146 DEBUG: View 3 : 0.540372670807
+2016-08-24 11:20:25,413 DEBUG: Best view : MiRNA__
+2016-08-24 11:20:31,776 DEBUG: Start: Iteration 101
+2016-08-24 11:20:31,794 DEBUG: View 0 : 0.496894409938
+2016-08-24 11:20:31,802 DEBUG: View 1 : 0.714285714286
+2016-08-24 11:20:31,895 DEBUG: View 2 : 0.503105590062
+2016-08-24 11:20:31,902 DEBUG: View 3 : 0.496894409938
+2016-08-24 11:20:32,172 DEBUG: Best view : MiRNA__
+2016-08-24 11:20:38,807 DEBUG: Start: Iteration 102
+2016-08-24 11:20:38,831 DEBUG: View 0 : 0.695652173913
+2016-08-24 11:20:38,843 DEBUG: View 1 : 0.403726708075
+2016-08-24 11:20:38,958 DEBUG: View 2 : 0.496894409938
+2016-08-24 11:20:38,968 DEBUG: View 3 : 0.683229813665
+2016-08-24 11:20:39,249 DEBUG: Best view : Clinic_
+2016-08-24 11:20:45,713 INFO: Start: Classification
+2016-08-24 11:21:01,314 INFO: Done: Fold number 1
+2016-08-24 11:21:01,314 INFO: Start: Fold number 2
+2016-08-24 11:21:02,941 DEBUG: Start: Iteration 1
+2016-08-24 11:21:02,957 DEBUG: View 0 : 0.615384615385
+2016-08-24 11:21:02,965 DEBUG: View 1 : 0.615384615385
+2016-08-24 11:21:03,052 DEBUG: View 2 : 0.615384615385
+2016-08-24 11:21:03,060 DEBUG: View 3 : 0.615384615385
+2016-08-24 11:21:03,101 DEBUG: Best view : Methyl_
+2016-08-24 11:21:03,178 DEBUG: Start: Iteration 2
+2016-08-24 11:21:03,195 DEBUG: View 0 : 0.557692307692
+2016-08-24 11:21:03,203 DEBUG: View 1 : 0.455128205128
+2016-08-24 11:21:03,294 DEBUG: View 2 : 0.576923076923
+2016-08-24 11:21:03,301 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:21:03,347 DEBUG: Best view : Clinic_
+2016-08-24 11:21:03,483 DEBUG: Start: Iteration 3
+2016-08-24 11:21:03,501 DEBUG: View 0 : 0.487179487179
+2016-08-24 11:21:03,509 DEBUG: View 1 : 0.570512820513
+2016-08-24 11:21:03,594 DEBUG: View 2 : 0.442307692308
+2016-08-24 11:21:03,602 DEBUG: View 3 : 0.474358974359
+2016-08-24 11:21:03,656 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:03,847 DEBUG: Start: Iteration 4
+2016-08-24 11:21:03,863 DEBUG: View 0 : 0.487179487179
+2016-08-24 11:21:03,871 DEBUG: View 1 : 0.628205128205
+2016-08-24 11:21:03,953 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:21:03,961 DEBUG: View 3 : 0.673076923077
+2016-08-24 11:21:04,015 DEBUG: Best view : Clinic_
+2016-08-24 11:21:04,261 DEBUG: Start: Iteration 5
+2016-08-24 11:21:04,278 DEBUG: View 0 : 0.467948717949
+2016-08-24 11:21:04,285 DEBUG: View 1 : 0.384615384615
+2016-08-24 11:21:04,372 DEBUG: View 2 : 0.589743589744
+2016-08-24 11:21:04,380 DEBUG: View 3 : 0.583333333333
+2016-08-24 11:21:04,437 DEBUG: Best view : RANSeq_
+2016-08-24 11:21:04,758 DEBUG: Start: Iteration 6
+2016-08-24 11:21:04,775 DEBUG: View 0 : 0.74358974359
+2016-08-24 11:21:04,783 DEBUG: View 1 : 0.538461538462
+2016-08-24 11:21:04,865 DEBUG: View 2 : 0.608974358974
+2016-08-24 11:21:04,873 DEBUG: View 3 : 0.544871794872
+2016-08-24 11:21:04,933 DEBUG: Best view : Methyl_
+2016-08-24 11:21:05,314 DEBUG: Start: Iteration 7
+2016-08-24 11:21:05,331 DEBUG: View 0 : 0.50641025641
+2016-08-24 11:21:05,338 DEBUG: View 1 : 0.628205128205
+2016-08-24 11:21:05,422 DEBUG: View 2 : 0.5
+2016-08-24 11:21:05,430 DEBUG: View 3 : 0.641025641026
+2016-08-24 11:21:05,491 DEBUG: Best view : Clinic_
+2016-08-24 11:21:05,935 DEBUG: Start: Iteration 8
+2016-08-24 11:21:05,952 DEBUG: View 0 : 0.487179487179
+2016-08-24 11:21:05,959 DEBUG: View 1 : 0.596153846154
+2016-08-24 11:21:06,054 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:21:06,063 DEBUG: View 3 : 0.557692307692
+2016-08-24 11:21:06,129 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:06,623 DEBUG: Start: Iteration 9
+2016-08-24 11:21:06,639 DEBUG: View 0 : 0.487179487179
+2016-08-24 11:21:06,647 DEBUG: View 1 : 0.596153846154
+2016-08-24 11:21:06,724 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:21:06,731 DEBUG: View 3 : 0.596153846154
+2016-08-24 11:21:06,797 DEBUG: Best view : Clinic_
+2016-08-24 11:21:07,345 DEBUG: Start: Iteration 10
+2016-08-24 11:21:07,367 DEBUG: View 0 : 0.653846153846
+2016-08-24 11:21:07,375 DEBUG: View 1 : 0.608974358974
+2016-08-24 11:21:07,458 DEBUG: View 2 : 0.634615384615
+2016-08-24 11:21:07,466 DEBUG: View 3 : 0.673076923077
+2016-08-24 11:21:07,533 DEBUG: Best view : Clinic_
+2016-08-24 11:21:08,137 DEBUG: Start: Iteration 11
+2016-08-24 11:21:08,153 DEBUG: View 0 : 0.49358974359
+2016-08-24 11:21:08,162 DEBUG: View 1 : 0.24358974359
+2016-08-24 11:21:08,271 DEBUG: View 2 : 0.519230769231
+2016-08-24 11:21:08,280 DEBUG: View 3 : 0.634615384615
+2016-08-24 11:21:08,355 DEBUG: Best view : Clinic_
+2016-08-24 11:21:09,028 DEBUG: Start: Iteration 12
+2016-08-24 11:21:09,044 DEBUG: View 0 : 0.602564102564
+2016-08-24 11:21:09,051 DEBUG: View 1 : 0.564102564103
+2016-08-24 11:21:09,139 DEBUG: View 2 : 0.557692307692
+2016-08-24 11:21:09,146 DEBUG: View 3 : 0.583333333333
+2016-08-24 11:21:09,228 DEBUG: Best view : Clinic_
+2016-08-24 11:21:09,951 DEBUG: Start: Iteration 13
+2016-08-24 11:21:09,968 DEBUG: View 0 : 0.679487179487
+2016-08-24 11:21:09,976 DEBUG: View 1 : 0.615384615385
+2016-08-24 11:21:10,058 DEBUG: View 2 : 0.596153846154
+2016-08-24 11:21:10,066 DEBUG: View 3 : 0.570512820513
+2016-08-24 11:21:10,140 DEBUG: Best view : Methyl_
+2016-08-24 11:21:10,927 DEBUG: Start: Iteration 14
+2016-08-24 11:21:10,943 DEBUG: View 0 : 0.564102564103
+2016-08-24 11:21:10,952 DEBUG: View 1 : 0.621794871795
+2016-08-24 11:21:11,038 DEBUG: View 2 : 0.557692307692
+2016-08-24 11:21:11,045 DEBUG: View 3 : 0.602564102564
+2016-08-24 11:21:11,122 DEBUG: Best view : Clinic_
+2016-08-24 11:21:11,968 DEBUG: Start: Iteration 15
+2016-08-24 11:21:11,985 DEBUG: View 0 : 0.551282051282
+2016-08-24 11:21:11,992 DEBUG: View 1 : 0.634615384615
+2016-08-24 11:21:12,074 DEBUG: View 2 : 0.467948717949
+2016-08-24 11:21:12,082 DEBUG: View 3 : 0.596153846154
+2016-08-24 11:21:12,161 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:13,061 DEBUG: Start: Iteration 16
+2016-08-24 11:21:13,078 DEBUG: View 0 : 0.679487179487
+2016-08-24 11:21:13,086 DEBUG: View 1 : 0.403846153846
+2016-08-24 11:21:13,172 DEBUG: View 2 : 0.628205128205
+2016-08-24 11:21:13,180 DEBUG: View 3 : 0.544871794872
+2016-08-24 11:21:13,262 DEBUG: Best view : Methyl_
+2016-08-24 11:21:14,233 DEBUG: Start: Iteration 17
+2016-08-24 11:21:14,250 DEBUG: View 0 : 0.621794871795
+2016-08-24 11:21:14,258 DEBUG: View 1 : 0.673076923077
+2016-08-24 11:21:14,340 DEBUG: View 2 : 0.602564102564
+2016-08-24 11:21:14,348 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:21:14,431 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:15,447 DEBUG: Start: Iteration 18
+2016-08-24 11:21:15,464 DEBUG: View 0 : 0.557692307692
+2016-08-24 11:21:15,471 DEBUG: View 1 : 0.641025641026
+2016-08-24 11:21:15,573 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:21:15,582 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:21:15,675 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:16,754 DEBUG: Start: Iteration 19
+2016-08-24 11:21:16,770 DEBUG: View 0 : 0.461538461538
+2016-08-24 11:21:16,777 DEBUG: View 1 : 0.647435897436
+2016-08-24 11:21:16,859 DEBUG: View 2 : 0.538461538462
+2016-08-24 11:21:16,866 DEBUG: View 3 : 0.551282051282
+2016-08-24 11:21:16,954 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:18,089 DEBUG: Start: Iteration 20
+2016-08-24 11:21:18,105 DEBUG: View 0 : 0.551282051282
+2016-08-24 11:21:18,113 DEBUG: View 1 : 0.371794871795
+2016-08-24 11:21:18,193 DEBUG: View 2 : 0.666666666667
+2016-08-24 11:21:18,201 DEBUG: View 3 : 0.596153846154
+2016-08-24 11:21:18,291 DEBUG: Best view : RANSeq_
+2016-08-24 11:21:19,495 DEBUG: Start: Iteration 21
+2016-08-24 11:21:19,512 DEBUG: View 0 : 0.365384615385
+2016-08-24 11:21:19,520 DEBUG: View 1 : 0.576923076923
+2016-08-24 11:21:19,609 DEBUG: View 2 : 0.557692307692
+2016-08-24 11:21:19,616 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:21:19,709 DEBUG: Best view : Clinic_
+2016-08-24 11:21:20,977 DEBUG: Start: Iteration 22
+2016-08-24 11:21:20,994 DEBUG: View 0 : 0.660256410256
+2016-08-24 11:21:21,002 DEBUG: View 1 : 0.782051282051
+2016-08-24 11:21:21,090 DEBUG: View 2 : 0.602564102564
+2016-08-24 11:21:21,097 DEBUG: View 3 : 0.538461538462
+2016-08-24 11:21:21,191 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:22,497 DEBUG: Start: Iteration 23
+2016-08-24 11:21:22,514 DEBUG: View 0 : 0.474358974359
+2016-08-24 11:21:22,522 DEBUG: View 1 : 0.314102564103
+2016-08-24 11:21:22,598 DEBUG: View 2 : 0.50641025641
+2016-08-24 11:21:22,605 DEBUG: View 3 : 0.602564102564
+2016-08-24 11:21:22,701 DEBUG: Best view : Clinic_
+2016-08-24 11:21:24,095 DEBUG: Start: Iteration 24
+2016-08-24 11:21:24,112 DEBUG: View 0 : 0.551282051282
+2016-08-24 11:21:24,120 DEBUG: View 1 : 0.429487179487
+2016-08-24 11:21:24,205 DEBUG: View 2 : 0.621794871795
+2016-08-24 11:21:24,214 DEBUG: View 3 : 0.653846153846
+2016-08-24 11:21:24,312 DEBUG: Best view : Clinic_
+2016-08-24 11:21:25,747 DEBUG: Start: Iteration 25
+2016-08-24 11:21:25,764 DEBUG: View 0 : 0.570512820513
+2016-08-24 11:21:25,772 DEBUG: View 1 : 0.519230769231
+2016-08-24 11:21:25,855 DEBUG: View 2 : 0.621794871795
+2016-08-24 11:21:25,863 DEBUG: View 3 : 0.596153846154
+2016-08-24 11:21:25,963 DEBUG: Best view : Clinic_
+2016-08-24 11:21:27,457 DEBUG: Start: Iteration 26
+2016-08-24 11:21:27,473 DEBUG: View 0 : 0.557692307692
+2016-08-24 11:21:27,481 DEBUG: View 1 : 0.378205128205
+2016-08-24 11:21:27,564 DEBUG: View 2 : 0.576923076923
+2016-08-24 11:21:27,572 DEBUG: View 3 : 0.692307692308
+2016-08-24 11:21:27,675 DEBUG: Best view : Clinic_
+2016-08-24 11:21:29,220 DEBUG: Start: Iteration 27
+2016-08-24 11:21:29,236 DEBUG: View 0 : 0.474358974359
+2016-08-24 11:21:29,244 DEBUG: View 1 : 0.564102564103
+2016-08-24 11:21:29,327 DEBUG: View 2 : 0.570512820513
+2016-08-24 11:21:29,335 DEBUG: View 3 : 0.564102564103
+2016-08-24 11:21:29,440 DEBUG: Best view : Clinic_
+2016-08-24 11:21:31,047 DEBUG: Start: Iteration 28
+2016-08-24 11:21:31,063 DEBUG: View 0 : 0.429487179487
+2016-08-24 11:21:31,071 DEBUG: View 1 : 0.75
+2016-08-24 11:21:31,155 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:21:31,162 DEBUG: View 3 : 0.602564102564
+2016-08-24 11:21:31,270 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:32,931 DEBUG: Start: Iteration 29
+2016-08-24 11:21:32,947 DEBUG: View 0 : 0.544871794872
+2016-08-24 11:21:32,955 DEBUG: View 1 : 0.576923076923
+2016-08-24 11:21:33,041 DEBUG: View 2 : 0.49358974359
+2016-08-24 11:21:33,049 DEBUG: View 3 : 0.5
+2016-08-24 11:21:33,161 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:34,897 DEBUG: Start: Iteration 30
+2016-08-24 11:21:34,914 DEBUG: View 0 : 0.615384615385
+2016-08-24 11:21:34,921 DEBUG: View 1 : 0.621794871795
+2016-08-24 11:21:35,009 DEBUG: View 2 : 0.448717948718
+2016-08-24 11:21:35,016 DEBUG: View 3 : 0.538461538462
+2016-08-24 11:21:35,130 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:36,907 DEBUG: Start: Iteration 31
+2016-08-24 11:21:36,923 DEBUG: View 0 : 0.480769230769
+2016-08-24 11:21:36,931 DEBUG: View 1 : 0.570512820513
+2016-08-24 11:21:37,013 DEBUG: View 2 : 0.589743589744
+2016-08-24 11:21:37,020 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:21:37,135 DEBUG: Best view : Clinic_
+2016-08-24 11:21:38,986 DEBUG: Start: Iteration 32
+2016-08-24 11:21:39,003 DEBUG: View 0 : 0.410256410256
+2016-08-24 11:21:39,011 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:21:39,094 DEBUG: View 2 : 0.570512820513
+2016-08-24 11:21:39,103 DEBUG: View 3 : 0.519230769231
+2016-08-24 11:21:39,220 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:41,118 DEBUG: Start: Iteration 33
+2016-08-24 11:21:41,134 DEBUG: View 0 : 0.339743589744
+2016-08-24 11:21:41,142 DEBUG: View 1 : 0.525641025641
+2016-08-24 11:21:41,217 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:21:41,225 DEBUG: View 3 : 0.442307692308
+2016-08-24 11:21:41,344 DEBUG: Best view : RANSeq_
+2016-08-24 11:21:43,320 DEBUG: Start: Iteration 34
+2016-08-24 11:21:43,336 DEBUG: View 0 : 0.519230769231
+2016-08-24 11:21:43,344 DEBUG: View 1 : 0.448717948718
+2016-08-24 11:21:43,426 DEBUG: View 2 : 0.628205128205
+2016-08-24 11:21:43,434 DEBUG: View 3 : 0.487179487179
+2016-08-24 11:21:43,554 DEBUG: Best view : RANSeq_
+2016-08-24 11:21:45,593 DEBUG: Start: Iteration 35
+2016-08-24 11:21:45,609 DEBUG: View 0 : 0.487179487179
+2016-08-24 11:21:45,617 DEBUG: View 1 : 0.673076923077
+2016-08-24 11:21:45,699 DEBUG: View 2 : 0.583333333333
+2016-08-24 11:21:45,707 DEBUG: View 3 : 0.576923076923
+2016-08-24 11:21:45,831 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:47,920 DEBUG: Start: Iteration 36
+2016-08-24 11:21:47,936 DEBUG: View 0 : 0.416666666667
+2016-08-24 11:21:47,944 DEBUG: View 1 : 0.435897435897
+2016-08-24 11:21:48,029 DEBUG: View 2 : 0.570512820513
+2016-08-24 11:21:48,037 DEBUG: View 3 : 0.679487179487
+2016-08-24 11:21:48,164 DEBUG: Best view : Clinic_
+2016-08-24 11:21:50,319 DEBUG: Start: Iteration 37
+2016-08-24 11:21:50,335 DEBUG: View 0 : 0.525641025641
+2016-08-24 11:21:50,343 DEBUG: View 1 : 0.602564102564
+2016-08-24 11:21:50,429 DEBUG: View 2 : 0.615384615385
+2016-08-24 11:21:50,437 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:21:50,563 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:52,782 DEBUG: Start: Iteration 38
+2016-08-24 11:21:52,799 DEBUG: View 0 : 0.480769230769
+2016-08-24 11:21:52,807 DEBUG: View 1 : 0.576923076923
+2016-08-24 11:21:52,889 DEBUG: View 2 : 0.570512820513
+2016-08-24 11:21:52,896 DEBUG: View 3 : 0.532051282051
+2016-08-24 11:21:53,028 DEBUG: Best view : MiRNA__
+2016-08-24 11:21:55,289 DEBUG: Start: Iteration 39
+2016-08-24 11:21:55,306 DEBUG: View 0 : 0.410256410256
+2016-08-24 11:21:55,314 DEBUG: View 1 : 0.557692307692
+2016-08-24 11:21:55,401 DEBUG: View 2 : 0.570512820513
+2016-08-24 11:21:55,409 DEBUG: View 3 : 0.532051282051
+2016-08-24 11:21:55,541 DEBUG: Best view : RANSeq_
+2016-08-24 11:21:57,876 DEBUG: Start: Iteration 40
+2016-08-24 11:21:57,892 DEBUG: View 0 : 0.423076923077
+2016-08-24 11:21:57,900 DEBUG: View 1 : 0.50641025641
+2016-08-24 11:21:57,985 DEBUG: View 2 : 0.602564102564
+2016-08-24 11:21:57,993 DEBUG: View 3 : 0.5
+2016-08-24 11:21:58,126 DEBUG: Best view : RANSeq_
+2016-08-24 11:22:00,528 DEBUG: Start: Iteration 41
+2016-08-24 11:22:00,545 DEBUG: View 0 : 0.711538461538
+2016-08-24 11:22:00,552 DEBUG: View 1 : 0.641025641026
+2016-08-24 11:22:00,634 DEBUG: View 2 : 0.634615384615
+2016-08-24 11:22:00,642 DEBUG: View 3 : 0.621794871795
+2016-08-24 11:22:00,779 DEBUG: Best view : Methyl_
+2016-08-24 11:22:03,239 DEBUG: Start: Iteration 42
+2016-08-24 11:22:03,255 DEBUG: View 0 : 0.480769230769
+2016-08-24 11:22:03,263 DEBUG: View 1 : 0.551282051282
+2016-08-24 11:22:03,353 DEBUG: View 2 : 0.544871794872
+2016-08-24 11:22:03,360 DEBUG: View 3 : 0.666666666667
+2016-08-24 11:22:03,500 DEBUG: Best view : Clinic_
+2016-08-24 11:22:06,015 DEBUG: Start: Iteration 43
+2016-08-24 11:22:06,031 DEBUG: View 0 : 0.551282051282
+2016-08-24 11:22:06,039 DEBUG: View 1 : 0.564102564103
+2016-08-24 11:22:06,124 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:22:06,132 DEBUG: View 3 : 0.641025641026
+2016-08-24 11:22:06,271 DEBUG: Best view : Clinic_
+2016-08-24 11:22:08,861 DEBUG: Start: Iteration 44
+2016-08-24 11:22:08,878 DEBUG: View 0 : 0.416666666667
+2016-08-24 11:22:08,885 DEBUG: View 1 : 0.647435897436
+2016-08-24 11:22:08,969 DEBUG: View 2 : 0.628205128205
+2016-08-24 11:22:08,976 DEBUG: View 3 : 0.660256410256
+2016-08-24 11:22:09,120 DEBUG: Best view : Clinic_
+2016-08-24 11:22:11,751 DEBUG: Start: Iteration 45
+2016-08-24 11:22:11,767 DEBUG: View 0 : 0.557692307692
+2016-08-24 11:22:11,775 DEBUG: View 1 : 0.365384615385
+2016-08-24 11:22:11,864 DEBUG: View 2 : 0.583333333333
+2016-08-24 11:22:11,871 DEBUG: View 3 : 0.525641025641
+2016-08-24 11:22:12,016 DEBUG: Best view : RANSeq_
+2016-08-24 11:22:14,742 DEBUG: Start: Iteration 46
+2016-08-24 11:22:14,758 DEBUG: View 0 : 0.570512820513
+2016-08-24 11:22:14,766 DEBUG: View 1 : 0.602564102564
+2016-08-24 11:22:14,854 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:22:14,861 DEBUG: View 3 : 0.628205128205
+2016-08-24 11:22:15,009 DEBUG: Best view : Clinic_
+2016-08-24 11:22:17,777 DEBUG: Start: Iteration 47
+2016-08-24 11:22:17,794 DEBUG: View 0 : 0.480769230769
+2016-08-24 11:22:17,802 DEBUG: View 1 : 0.320512820513
+2016-08-24 11:22:17,884 DEBUG: View 2 : 0.49358974359
+2016-08-24 11:22:17,891 DEBUG: View 3 : 0.461538461538
+2016-08-24 11:22:17,891 WARNING: WARNING: All bad for iteration 46
+2016-08-24 11:22:18,042 DEBUG: Best view : RANSeq_
+2016-08-24 11:22:20,878 DEBUG: Start: Iteration 48
+2016-08-24 11:22:20,895 DEBUG: View 0 : 0.544871794872
+2016-08-24 11:22:20,902 DEBUG: View 1 : 0.397435897436
+2016-08-24 11:22:20,985 DEBUG: View 2 : 0.589743589744
+2016-08-24 11:22:20,993 DEBUG: View 3 : 0.621794871795
+2016-08-24 11:22:21,144 DEBUG: Best view : Clinic_
+2016-08-24 11:22:24,050 DEBUG: Start: Iteration 49
+2016-08-24 11:22:24,066 DEBUG: View 0 : 0.589743589744
+2016-08-24 11:22:24,074 DEBUG: View 1 : 0.333333333333
+2016-08-24 11:22:24,159 DEBUG: View 2 : 0.544871794872
+2016-08-24 11:22:24,166 DEBUG: View 3 : 0.512820512821
+2016-08-24 11:22:24,321 DEBUG: Best view : Methyl_
+2016-08-24 11:22:27,282 DEBUG: Start: Iteration 50
+2016-08-24 11:22:27,298 DEBUG: View 0 : 0.50641025641
+2016-08-24 11:22:27,306 DEBUG: View 1 : 0.576923076923
+2016-08-24 11:22:27,388 DEBUG: View 2 : 0.583333333333
+2016-08-24 11:22:27,396 DEBUG: View 3 : 0.589743589744
+2016-08-24 11:22:27,554 DEBUG: Best view : Clinic_
+2016-08-24 11:22:30,568 DEBUG: Start: Iteration 51
+2016-08-24 11:22:30,585 DEBUG: View 0 : 0.429487179487
+2016-08-24 11:22:30,592 DEBUG: View 1 : 0.423076923077
+2016-08-24 11:22:30,681 DEBUG: View 2 : 0.596153846154
+2016-08-24 11:22:30,688 DEBUG: View 3 : 0.583333333333
+2016-08-24 11:22:30,847 DEBUG: Best view : RANSeq_
+2016-08-24 11:22:33,933 DEBUG: Start: Iteration 52
+2016-08-24 11:22:33,950 DEBUG: View 0 : 0.570512820513
+2016-08-24 11:22:33,957 DEBUG: View 1 : 0.653846153846
+2016-08-24 11:22:34,040 DEBUG: View 2 : 0.615384615385
+2016-08-24 11:22:34,048 DEBUG: View 3 : 0.49358974359
+2016-08-24 11:22:34,211 DEBUG: Best view : MiRNA__
+2016-08-24 11:22:37,353 DEBUG: Start: Iteration 53
+2016-08-24 11:22:37,370 DEBUG: View 0 : 0.538461538462
+2016-08-24 11:22:37,378 DEBUG: View 1 : 0.628205128205
+2016-08-24 11:22:37,465 DEBUG: View 2 : 0.653846153846
+2016-08-24 11:22:37,473 DEBUG: View 3 : 0.525641025641
+2016-08-24 11:22:37,635 DEBUG: Best view : RANSeq_
+2016-08-24 11:22:40,837 DEBUG: Start: Iteration 54
+2016-08-24 11:22:40,854 DEBUG: View 0 : 0.589743589744
+2016-08-24 11:22:40,862 DEBUG: View 1 : 0.448717948718
+2016-08-24 11:22:40,943 DEBUG: View 2 : 0.50641025641
+2016-08-24 11:22:40,951 DEBUG: View 3 : 0.583333333333
+2016-08-24 11:22:41,117 DEBUG: Best view : Clinic_
+2016-08-24 11:22:44,382 DEBUG: Start: Iteration 55
+2016-08-24 11:22:44,398 DEBUG: View 0 : 0.634615384615
+2016-08-24 11:22:44,406 DEBUG: View 1 : 0.551282051282
+2016-08-24 11:22:44,485 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:22:44,493 DEBUG: View 3 : 0.448717948718
+2016-08-24 11:22:44,658 DEBUG: Best view : Methyl_
+2016-08-24 11:22:47,984 DEBUG: Start: Iteration 56
+2016-08-24 11:22:48,000 DEBUG: View 0 : 0.544871794872
+2016-08-24 11:22:48,008 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:22:48,091 DEBUG: View 2 : 0.525641025641
+2016-08-24 11:22:48,099 DEBUG: View 3 : 0.589743589744
+2016-08-24 11:22:48,265 DEBUG: Best view : MiRNA__
+2016-08-24 11:22:51,652 DEBUG: Start: Iteration 57
+2016-08-24 11:22:51,668 DEBUG: View 0 : 0.583333333333
+2016-08-24 11:22:51,676 DEBUG: View 1 : 0.397435897436
+2016-08-24 11:22:51,769 DEBUG: View 2 : 0.519230769231
+2016-08-24 11:22:51,776 DEBUG: View 3 : 0.538461538462
+2016-08-24 11:22:51,945 DEBUG: Best view : Methyl_
+2016-08-24 11:22:55,390 DEBUG: Start: Iteration 58
+2016-08-24 11:22:55,406 DEBUG: View 0 : 0.403846153846
+2016-08-24 11:22:55,414 DEBUG: View 1 : 0.410256410256
+2016-08-24 11:22:55,502 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:22:55,510 DEBUG: View 3 : 0.602564102564
+2016-08-24 11:22:55,681 DEBUG: Best view : Clinic_
+2016-08-24 11:22:59,217 DEBUG: Start: Iteration 59
+2016-08-24 11:22:59,234 DEBUG: View 0 : 0.474358974359
+2016-08-24 11:22:59,242 DEBUG: View 1 : 0.512820512821
+2016-08-24 11:22:59,326 DEBUG: View 2 : 0.608974358974
+2016-08-24 11:22:59,333 DEBUG: View 3 : 0.512820512821
+2016-08-24 11:22:59,507 DEBUG: Best view : RANSeq_
+2016-08-24 11:23:03,084 DEBUG: Start: Iteration 60
+2016-08-24 11:23:03,101 DEBUG: View 0 : 0.397435897436
+2016-08-24 11:23:03,110 DEBUG: View 1 : 0.455128205128
+2016-08-24 11:23:03,196 DEBUG: View 2 : 0.653846153846
+2016-08-24 11:23:03,204 DEBUG: View 3 : 0.570512820513
+2016-08-24 11:23:03,381 DEBUG: Best view : RANSeq_
+2016-08-24 11:23:07,042 DEBUG: Start: Iteration 61
+2016-08-24 11:23:07,059 DEBUG: View 0 : 0.705128205128
+2016-08-24 11:23:07,066 DEBUG: View 1 : 0.442307692308
+2016-08-24 11:23:07,154 DEBUG: View 2 : 0.557692307692
+2016-08-24 11:23:07,162 DEBUG: View 3 : 0.621794871795
+2016-08-24 11:23:07,340 DEBUG: Best view : Methyl_
+2016-08-24 11:23:11,059 DEBUG: Start: Iteration 62
+2016-08-24 11:23:11,075 DEBUG: View 0 : 0.391025641026
+2016-08-24 11:23:11,083 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:23:11,180 DEBUG: View 2 : 0.532051282051
+2016-08-24 11:23:11,188 DEBUG: View 3 : 0.570512820513
+2016-08-24 11:23:11,379 DEBUG: Best view : MiRNA__
+2016-08-24 11:23:15,148 DEBUG: Start: Iteration 63
+2016-08-24 11:23:15,164 DEBUG: View 0 : 0.384615384615
+2016-08-24 11:23:15,172 DEBUG: View 1 : 0.532051282051
+2016-08-24 11:23:15,256 DEBUG: View 2 : 0.49358974359
+2016-08-24 11:23:15,263 DEBUG: View 3 : 0.653846153846
+2016-08-24 11:23:15,447 DEBUG: Best view : Clinic_
+2016-08-24 11:23:19,280 DEBUG: Start: Iteration 64
+2016-08-24 11:23:19,296 DEBUG: View 0 : 0.551282051282
+2016-08-24 11:23:19,304 DEBUG: View 1 : 0.679487179487
+2016-08-24 11:23:19,391 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:23:19,398 DEBUG: View 3 : 0.583333333333
+2016-08-24 11:23:19,582 DEBUG: Best view : MiRNA__
+2016-08-24 11:23:23,489 DEBUG: Start: Iteration 65
+2016-08-24 11:23:23,505 DEBUG: View 0 : 0.583333333333
+2016-08-24 11:23:23,513 DEBUG: View 1 : 0.525641025641
+2016-08-24 11:23:23,597 DEBUG: View 2 : 0.602564102564
+2016-08-24 11:23:23,604 DEBUG: View 3 : 0.602564102564
+2016-08-24 11:23:23,795 DEBUG: Best view : Clinic_
+2016-08-24 11:23:27,722 DEBUG: Start: Iteration 66
+2016-08-24 11:23:27,739 DEBUG: View 0 : 0.538461538462
+2016-08-24 11:23:27,746 DEBUG: View 1 : 0.538461538462
+2016-08-24 11:23:27,833 DEBUG: View 2 : 0.525641025641
+2016-08-24 11:23:27,840 DEBUG: View 3 : 0.5
+2016-08-24 11:23:28,046 DEBUG: Best view : MiRNA__
+2016-08-24 11:23:32,077 DEBUG: Start: Iteration 67
+2016-08-24 11:23:32,094 DEBUG: View 0 : 0.403846153846
+2016-08-24 11:23:32,102 DEBUG: View 1 : 0.49358974359
+2016-08-24 11:23:32,186 DEBUG: View 2 : 0.448717948718
+2016-08-24 11:23:32,194 DEBUG: View 3 : 0.615384615385
+2016-08-24 11:23:32,386 DEBUG: Best view : Clinic_
+2016-08-24 11:23:36,441 DEBUG: Start: Iteration 68
+2016-08-24 11:23:36,458 DEBUG: View 0 : 0.660256410256
+2016-08-24 11:23:36,466 DEBUG: View 1 : 0.339743589744
+2016-08-24 11:23:36,553 DEBUG: View 2 : 0.621794871795
+2016-08-24 11:23:36,560 DEBUG: View 3 : 0.685897435897
+2016-08-24 11:23:36,754 DEBUG: Best view : Clinic_
+2016-08-24 11:23:40,869 DEBUG: Start: Iteration 69
+2016-08-24 11:23:40,885 DEBUG: View 0 : 0.602564102564
+2016-08-24 11:23:40,893 DEBUG: View 1 : 0.442307692308
+2016-08-24 11:23:40,971 DEBUG: View 2 : 0.570512820513
+2016-08-24 11:23:40,979 DEBUG: View 3 : 0.596153846154
+2016-08-24 11:23:41,173 DEBUG: Best view : Clinic_
+2016-08-24 11:23:45,325 DEBUG: Start: Iteration 70
+2016-08-24 11:23:45,341 DEBUG: View 0 : 0.435897435897
+2016-08-24 11:23:45,349 DEBUG: View 1 : 0.525641025641
+2016-08-24 11:23:45,436 DEBUG: View 2 : 0.525641025641
+2016-08-24 11:23:45,443 DEBUG: View 3 : 0.621794871795
+2016-08-24 11:23:45,641 DEBUG: Best view : Clinic_
+2016-08-24 11:23:49,870 DEBUG: Start: Iteration 71
+2016-08-24 11:23:49,887 DEBUG: View 0 : 0.551282051282
+2016-08-24 11:23:49,895 DEBUG: View 1 : 0.621794871795
+2016-08-24 11:23:49,978 DEBUG: View 2 : 0.538461538462
+2016-08-24 11:23:49,986 DEBUG: View 3 : 0.634615384615
+2016-08-24 11:23:50,196 DEBUG: Best view : Clinic_
+2016-08-24 11:23:54,507 DEBUG: Start: Iteration 72
+2016-08-24 11:23:54,523 DEBUG: View 0 : 0.512820512821
+2016-08-24 11:23:54,531 DEBUG: View 1 : 0.455128205128
+2016-08-24 11:23:54,611 DEBUG: View 2 : 0.532051282051
+2016-08-24 11:23:54,619 DEBUG: View 3 : 0.551282051282
+2016-08-24 11:23:54,820 DEBUG: Best view : Clinic_
+2016-08-24 11:23:59,164 DEBUG: Start: Iteration 73
+2016-08-24 11:23:59,180 DEBUG: View 0 : 0.416666666667
+2016-08-24 11:23:59,188 DEBUG: View 1 : 0.474358974359
+2016-08-24 11:23:59,273 DEBUG: View 2 : 0.5
+2016-08-24 11:23:59,280 DEBUG: View 3 : 0.525641025641
+2016-08-24 11:23:59,485 DEBUG: Best view : Clinic_
+2016-08-24 11:24:03,917 DEBUG: Start: Iteration 74
+2016-08-24 11:24:03,934 DEBUG: View 0 : 0.564102564103
+2016-08-24 11:24:03,942 DEBUG: View 1 : 0.698717948718
+2016-08-24 11:24:04,029 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:24:04,037 DEBUG: View 3 : 0.5
+2016-08-24 11:24:04,257 DEBUG: Best view : MiRNA__
+2016-08-24 11:24:08,879 DEBUG: Start: Iteration 75
+2016-08-24 11:24:08,896 DEBUG: View 0 : 0.647435897436
+2016-08-24 11:24:08,904 DEBUG: View 1 : 0.397435897436
+2016-08-24 11:24:08,992 DEBUG: View 2 : 0.589743589744
+2016-08-24 11:24:09,000 DEBUG: View 3 : 0.583333333333
+2016-08-24 11:24:09,218 DEBUG: Best view : Methyl_
+2016-08-24 11:24:13,834 DEBUG: Start: Iteration 76
+2016-08-24 11:24:13,851 DEBUG: View 0 : 0.564102564103
+2016-08-24 11:24:13,859 DEBUG: View 1 : 0.75
+2016-08-24 11:24:13,949 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:24:13,957 DEBUG: View 3 : 0.602564102564
+2016-08-24 11:24:14,181 DEBUG: Best view : MiRNA__
+2016-08-24 11:24:18,999 DEBUG: Start: Iteration 77
+2016-08-24 11:24:19,016 DEBUG: View 0 : 0.641025641026
+2016-08-24 11:24:19,023 DEBUG: View 1 : 0.673076923077
+2016-08-24 11:24:19,111 DEBUG: View 2 : 0.519230769231
+2016-08-24 11:24:19,119 DEBUG: View 3 : 0.544871794872
+2016-08-24 11:24:19,332 DEBUG: Best view : MiRNA__
+2016-08-24 11:24:24,134 DEBUG: Start: Iteration 78
+2016-08-24 11:24:24,151 DEBUG: View 0 : 0.397435897436
+2016-08-24 11:24:24,159 DEBUG: View 1 : 0.282051282051
+2016-08-24 11:24:24,256 DEBUG: View 2 : 0.589743589744
+2016-08-24 11:24:24,264 DEBUG: View 3 : 0.653846153846
+2016-08-24 11:24:24,481 DEBUG: Best view : Clinic_
+2016-08-24 11:24:29,491 DEBUG: Start: Iteration 79
+2016-08-24 11:24:29,508 DEBUG: View 0 : 0.487179487179
+2016-08-24 11:24:29,516 DEBUG: View 1 : 0.564102564103
+2016-08-24 11:24:29,610 DEBUG: View 2 : 0.512820512821
+2016-08-24 11:24:29,618 DEBUG: View 3 : 0.621794871795
+2016-08-24 11:24:29,840 DEBUG: Best view : Clinic_
+2016-08-24 11:24:34,815 DEBUG: Start: Iteration 80
+2016-08-24 11:24:34,835 DEBUG: View 0 : 0.435897435897
+2016-08-24 11:24:34,844 DEBUG: View 1 : 0.711538461538
+2016-08-24 11:24:34,954 DEBUG: View 2 : 0.544871794872
+2016-08-24 11:24:34,964 DEBUG: View 3 : 0.551282051282
+2016-08-24 11:24:35,235 DEBUG: Best view : MiRNA__
+2016-08-24 11:24:40,456 DEBUG: Start: Iteration 81
+2016-08-24 11:24:40,474 DEBUG: View 0 : 0.576923076923
+2016-08-24 11:24:40,483 DEBUG: View 1 : 0.346153846154
+2016-08-24 11:24:40,571 DEBUG: View 2 : 0.557692307692
+2016-08-24 11:24:40,579 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:24:40,814 DEBUG: Best view : Clinic_
+2016-08-24 11:24:45,879 DEBUG: Start: Iteration 82
+2016-08-24 11:24:45,896 DEBUG: View 0 : 0.474358974359
+2016-08-24 11:24:45,905 DEBUG: View 1 : 0.50641025641
+2016-08-24 11:24:45,988 DEBUG: View 2 : 0.653846153846
+2016-08-24 11:24:45,996 DEBUG: View 3 : 0.641025641026
+2016-08-24 11:24:46,222 DEBUG: Best view : RANSeq_
+2016-08-24 11:24:51,238 DEBUG: Start: Iteration 83
+2016-08-24 11:24:51,255 DEBUG: View 0 : 0.544871794872
+2016-08-24 11:24:51,264 DEBUG: View 1 : 0.692307692308
+2016-08-24 11:24:51,355 DEBUG: View 2 : 0.576923076923
+2016-08-24 11:24:51,363 DEBUG: View 3 : 0.602564102564
+2016-08-24 11:24:51,591 DEBUG: Best view : MiRNA__
+2016-08-24 11:24:56,849 DEBUG: Start: Iteration 84
+2016-08-24 11:24:56,866 DEBUG: View 0 : 0.602564102564
+2016-08-24 11:24:56,873 DEBUG: View 1 : 0.320512820513
+2016-08-24 11:24:56,962 DEBUG: View 2 : 0.647435897436
+2016-08-24 11:24:56,970 DEBUG: View 3 : 0.576923076923
+2016-08-24 11:24:57,226 DEBUG: Best view : RANSeq_
+2016-08-24 11:25:02,537 DEBUG: Start: Iteration 85
+2016-08-24 11:25:02,553 DEBUG: View 0 : 0.525641025641
+2016-08-24 11:25:02,561 DEBUG: View 1 : 0.615384615385
+2016-08-24 11:25:02,650 DEBUG: View 2 : 0.519230769231
+2016-08-24 11:25:02,657 DEBUG: View 3 : 0.660256410256
+2016-08-24 11:25:02,885 DEBUG: Best view : Clinic_
+2016-08-24 11:25:08,095 DEBUG: Start: Iteration 86
+2016-08-24 11:25:08,112 DEBUG: View 0 : 0.647435897436
+2016-08-24 11:25:08,120 DEBUG: View 1 : 0.525641025641
+2016-08-24 11:25:08,210 DEBUG: View 2 : 0.557692307692
+2016-08-24 11:25:08,218 DEBUG: View 3 : 0.641025641026
+2016-08-24 11:25:08,454 DEBUG: Best view : Clinic_
+2016-08-24 11:25:13,805 DEBUG: Start: Iteration 87
+2016-08-24 11:25:13,829 DEBUG: View 0 : 0.480769230769
+2016-08-24 11:25:13,844 DEBUG: View 1 : 0.628205128205
+2016-08-24 11:25:13,984 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:25:13,998 DEBUG: View 3 : 0.49358974359
+2016-08-24 11:25:14,388 DEBUG: Best view : MiRNA__
+2016-08-24 11:25:19,842 DEBUG: Start: Iteration 88
+2016-08-24 11:25:19,859 DEBUG: View 0 : 0.583333333333
+2016-08-24 11:25:19,867 DEBUG: View 1 : 0.480769230769
+2016-08-24 11:25:19,951 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:25:19,959 DEBUG: View 3 : 0.628205128205
+2016-08-24 11:25:20,266 DEBUG: Best view : Clinic_
+2016-08-24 11:25:25,733 DEBUG: Start: Iteration 89
+2016-08-24 11:25:25,749 DEBUG: View 0 : 0.544871794872
+2016-08-24 11:25:25,757 DEBUG: View 1 : 0.634615384615
+2016-08-24 11:25:25,843 DEBUG: View 2 : 0.50641025641
+2016-08-24 11:25:25,851 DEBUG: View 3 : 0.49358974359
+2016-08-24 11:25:26,091 DEBUG: Best view : MiRNA__
+2016-08-24 11:25:31,511 DEBUG: Start: Iteration 90
+2016-08-24 11:25:31,527 DEBUG: View 0 : 0.615384615385
+2016-08-24 11:25:31,535 DEBUG: View 1 : 0.685897435897
+2016-08-24 11:25:31,618 DEBUG: View 2 : 0.519230769231
+2016-08-24 11:25:31,626 DEBUG: View 3 : 0.564102564103
+2016-08-24 11:25:31,867 DEBUG: Best view : MiRNA__
+2016-08-24 11:25:37,241 DEBUG: Start: Iteration 91
+2016-08-24 11:25:37,257 DEBUG: View 0 : 0.50641025641
+2016-08-24 11:25:37,265 DEBUG: View 1 : 0.692307692308
+2016-08-24 11:25:37,352 DEBUG: View 2 : 0.557692307692
+2016-08-24 11:25:37,360 DEBUG: View 3 : 0.538461538462
+2016-08-24 11:25:37,600 DEBUG: Best view : MiRNA__
+2016-08-24 11:25:43,043 DEBUG: Start: Iteration 92
+2016-08-24 11:25:43,059 DEBUG: View 0 : 0.544871794872
+2016-08-24 11:25:43,067 DEBUG: View 1 : 0.474358974359
+2016-08-24 11:25:43,154 DEBUG: View 2 : 0.615384615385
+2016-08-24 11:25:43,162 DEBUG: View 3 : 0.634615384615
+2016-08-24 11:25:43,406 DEBUG: Best view : Clinic_
+2016-08-24 11:25:48,939 DEBUG: Start: Iteration 93
+2016-08-24 11:25:48,956 DEBUG: View 0 : 0.538461538462
+2016-08-24 11:25:48,964 DEBUG: View 1 : 0.589743589744
+2016-08-24 11:25:49,051 DEBUG: View 2 : 0.621794871795
+2016-08-24 11:25:49,058 DEBUG: View 3 : 0.570512820513
+2016-08-24 11:25:49,305 DEBUG: Best view : RANSeq_
+2016-08-24 11:25:54,890 DEBUG: Start: Iteration 94
+2016-08-24 11:25:54,907 DEBUG: View 0 : 0.435897435897
+2016-08-24 11:25:54,914 DEBUG: View 1 : 0.589743589744
+2016-08-24 11:25:54,997 DEBUG: View 2 : 0.5
+2016-08-24 11:25:55,004 DEBUG: View 3 : 0.608974358974
+2016-08-24 11:25:55,251 DEBUG: Best view : Clinic_
+2016-08-24 11:26:01,345 DEBUG: Start: Iteration 95
+2016-08-24 11:26:01,363 DEBUG: View 0 : 0.570512820513
+2016-08-24 11:26:01,371 DEBUG: View 1 : 0.448717948718
+2016-08-24 11:26:01,460 DEBUG: View 2 : 0.564102564103
+2016-08-24 11:26:01,468 DEBUG: View 3 : 0.544871794872
+2016-08-24 11:26:01,722 DEBUG: Best view : Clinic_
+2016-08-24 11:26:07,817 DEBUG: Start: Iteration 96
+2016-08-24 11:26:07,833 DEBUG: View 0 : 0.602564102564
+2016-08-24 11:26:07,841 DEBUG: View 1 : 0.410256410256
+2016-08-24 11:26:07,923 DEBUG: View 2 : 0.641025641026
+2016-08-24 11:26:07,931 DEBUG: View 3 : 0.653846153846
+2016-08-24 11:26:08,195 DEBUG: Best view : Clinic_
+2016-08-24 11:26:14,008 DEBUG: Start: Iteration 97
+2016-08-24 11:26:14,024 DEBUG: View 0 : 0.596153846154
+2016-08-24 11:26:14,032 DEBUG: View 1 : 0.384615384615
+2016-08-24 11:26:14,119 DEBUG: View 2 : 0.519230769231
+2016-08-24 11:26:14,126 DEBUG: View 3 : 0.621794871795
+2016-08-24 11:26:14,382 DEBUG: Best view : Clinic_
+2016-08-24 11:26:20,301 DEBUG: Start: Iteration 98
+2016-08-24 11:26:20,318 DEBUG: View 0 : 0.621794871795
+2016-08-24 11:26:20,326 DEBUG: View 1 : 0.391025641026
+2016-08-24 11:26:20,418 DEBUG: View 2 : 0.596153846154
+2016-08-24 11:26:20,426 DEBUG: View 3 : 0.653846153846
+2016-08-24 11:26:20,686 DEBUG: Best view : Clinic_
+2016-08-24 11:26:26,648 DEBUG: Start: Iteration 99
+2016-08-24 11:26:26,664 DEBUG: View 0 : 0.615384615385
+2016-08-24 11:26:26,672 DEBUG: View 1 : 0.391025641026
+2016-08-24 11:26:26,757 DEBUG: View 2 : 0.544871794872
+2016-08-24 11:26:26,765 DEBUG: View 3 : 0.628205128205
+2016-08-24 11:26:27,027 DEBUG: Best view : Clinic_
+2016-08-24 11:26:33,016 DEBUG: Start: Iteration 100
+2016-08-24 11:26:33,032 DEBUG: View 0 : 0.628205128205
+2016-08-24 11:26:33,040 DEBUG: View 1 : 0.602564102564
+2016-08-24 11:26:33,124 DEBUG: View 2 : 0.480769230769
+2016-08-24 11:26:33,132 DEBUG: View 3 : 0.647435897436
+2016-08-24 11:26:33,395 DEBUG: Best view : Clinic_
+2016-08-24 11:26:39,429 DEBUG: Start: Iteration 101
+2016-08-24 11:26:39,446 DEBUG: View 0 : 0.717948717949
+2016-08-24 11:26:39,453 DEBUG: View 1 : 0.634615384615
+2016-08-24 11:26:39,539 DEBUG: View 2 : 0.589743589744
+2016-08-24 11:26:39,546 DEBUG: View 3 : 0.628205128205
+2016-08-24 11:26:39,811 DEBUG: Best view : Methyl_
+2016-08-24 11:26:46,118 DEBUG: Start: Iteration 102
+2016-08-24 11:26:46,139 DEBUG: View 0 : 0.615384615385
+2016-08-24 11:26:46,148 DEBUG: View 1 : 0.628205128205
+2016-08-24 11:26:46,237 DEBUG: View 2 : 0.551282051282
+2016-08-24 11:26:46,244 DEBUG: View 3 : 0.634615384615
+2016-08-24 11:26:46,518 DEBUG: Best view : Clinic_
+2016-08-24 11:26:52,740 INFO: Start: Classification
+2016-08-24 11:27:08,084 INFO: Done: Fold number 2
+2016-08-24 11:27:08,084 INFO: Done: Classification
+2016-08-24 11:27:08,084 INFO: Info: Time for Classification: 742[s]
+2016-08-24 11:27:08,084 INFO: Start: Result Analysis for Mumbo
+2016-08-24 11:27:43,126 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 79.5150501672
+ -On Test : 79.9180327869
+ -On Validation : 83.9805825243
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1, sub-sampled at 0.02 on Methyl
+ -DecisionTree with depth 1, sub-sampled at 0.02 on MiRNA
+ -DecisionTree with depth 1, sub-sampled at 0.1 on RNASEQ
+ -DecisionTree with depth 2, sub-sampled at 0.1 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0566086956522
+ - Percentage of time chosen : 0.91
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0601552795031
+ - Percentage of time chosen : 0.031
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0589378881988
+ - Percentage of time chosen : 0.021
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0603664596273
+ - Percentage of time chosen : 0.038
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0546346153846
+ - Percentage of time chosen : 0.909
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.05475
+ - Percentage of time chosen : 0.028
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0575833333333
+ - Percentage of time chosen : 0.015
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0597243589744
+ - Percentage of time chosen : 0.048
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 72.6708074534
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 60.8974358974
+ Accuracy on test : 53.2786885246
+ Accuracy on validation : 63.1067961165
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 66.7841216754
+ Accuracy on test : 65.5737704918
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 72.6708074534
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 60.8974358974
+ Accuracy on test : 53.2786885246
+ Accuracy on validation : 63.1067961165
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 66.7841216754
+ Accuracy on test : 65.5737704918
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 72.6708074534
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 59.0163934426
+ Accuracy on validation : 65.0485436893
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 69.3482242395
+ Accuracy on test : 70.9016393443
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 71.4285714286
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.2307692308
+ Accuracy on test : 63.9344262295
+ Accuracy on validation : 66.0194174757
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 70.3296703297
+ Accuracy on test : 72.5409836066
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 71.4285714286
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 78.8461538462
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 75.1373626374
+ Accuracy on test : 75.4098360656
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 75.7763975155
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 78.2051282051
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 76.9907628603
+ Accuracy on test : 78.6885245902
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 75.1552795031
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 77.6699029126
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 78.2051282051
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 81.5533980583
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 76.6802038541
+ Accuracy on test : 76.6393442623
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 73.9130434783
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.4871794872
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 76.7001114827
+ Accuracy on test : 76.2295081967
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 75.7763975155
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 75.641025641
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 75.7087115783
+ Accuracy on test : 77.868852459
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 75.7763975155
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.9230769231
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 76.3497372193
+ Accuracy on test : 78.6885245902
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 76.397515528
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 75.641025641
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 78.640776699
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 76.0192705845
+ Accuracy on test : 79.0983606557
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 78.2608695652
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 78.640776699
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 77.5641025641
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 80.5825242718
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 77.9124860647
+ Accuracy on test : 77.868852459
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 77.0186335404
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 77.5641025641
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 77.2913680522
+ Accuracy on test : 77.4590163934
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 76.397515528
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 75.641025641
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 76.0192705845
+ Accuracy on test : 79.0983606557
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 75.7763975155
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 77.6699029126
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 80.1282051282
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 81.5533980583
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 77.9523013219
+ Accuracy on test : 79.5081967213
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 76.397515528
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 78.2051282051
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.3013218665
+ Accuracy on test : 82.7868852459
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 77.0186335404
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.4871794872
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 81.5533980583
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.2529065138
+ Accuracy on test : 82.3770491803
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 78.2608695652
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 81.4102564103
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.8355629877
+ Accuracy on test : 82.7868852459
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 78.2608695652
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 80.1282051282
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 81.5533980583
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 79.1945373467
+ Accuracy on test : 81.1475409836
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 78.2608695652
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.4871794872
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 78.8740245262
+ Accuracy on test : 83.1967213115
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 77.6397515528
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.5641025641
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 79.6116504854
+ Selected View : MiRNA__
+ - Mean :
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+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 964
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 965
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 966
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 967
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 968
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 969
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 970
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 971
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 972
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 973
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 974
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 975
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 976
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 977
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 978
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 979
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 980
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 981
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 982
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 983
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 984
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 985
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 986
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 987
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 988
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 989
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:06:00 0:00:15
+ Fold 2 0:12:07 0:00:15
+ Total 0:18:07 0:00:30
+ So a total classification time of 0:12:22.
+
+
+2016-08-24 11:27:43,912 INFO: Done: Result Analysis
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112743Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112743Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..99905780bc6d41f53313eea5bf9caed8e7a46e4f
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112743Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112743Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112743Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..31e85005079d3bdf782c4b00392bcf1ae5018187
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112743Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
@@ -0,0 +1,14060 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 79.5150501672
+ -On Test : 79.9180327869
+ -On Validation : 83.9805825243
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1, sub-sampled at 0.02 on Methyl
+ -DecisionTree with depth 1, sub-sampled at 0.02 on MiRNA
+ -DecisionTree with depth 1, sub-sampled at 0.1 on RNASEQ
+ -DecisionTree with depth 2, sub-sampled at 0.1 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0566086956522
+ - Percentage of time chosen : 0.91
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0601552795031
+ - Percentage of time chosen : 0.031
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0589378881988
+ - Percentage of time chosen : 0.021
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0603664596273
+ - Percentage of time chosen : 0.038
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0546346153846
+ - Percentage of time chosen : 0.909
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.05475
+ - Percentage of time chosen : 0.028
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0575833333333
+ - Percentage of time chosen : 0.015
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0597243589744
+ - Percentage of time chosen : 0.048
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 62.7329192547
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 61.5384615385
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 72.6708074534
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 60.8974358974
+ Accuracy on test : 53.2786885246
+ Accuracy on validation : 63.1067961165
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 66.7841216754
+ Accuracy on test : 65.5737704918
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 72.6708074534
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 74.7572815534
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 60.8974358974
+ Accuracy on test : 53.2786885246
+ Accuracy on validation : 63.1067961165
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 66.7841216754
+ Accuracy on test : 65.5737704918
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 72.6708074534
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 77.6699029126
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 66.0256410256
+ Accuracy on test : 59.0163934426
+ Accuracy on validation : 65.0485436893
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 69.3482242395
+ Accuracy on test : 70.9016393443
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 71.4285714286
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 69.2307692308
+ Accuracy on test : 63.9344262295
+ Accuracy on validation : 66.0194174757
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 70.3296703297
+ Accuracy on test : 72.5409836066
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 71.4285714286
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 76.6990291262
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 78.8461538462
+ Accuracy on test : 69.6721311475
+ Accuracy on validation : 79.6116504854
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 75.1373626374
+ Accuracy on test : 75.4098360656
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 75.7763975155
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 77.6699029126
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 78.2051282051
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 76.9907628603
+ Accuracy on test : 78.6885245902
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 75.1552795031
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+ - Iteration 1000
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+ - Mean :
+ Accuracy on train : 62.1356903966
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:06:00 0:00:15
+ Fold 2 0:12:07 0:00:15
+ Total 0:18:07 0:00:30
+ So a total classification time of 0:12:22.
+
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112821-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112821-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..302346851e6600ebdbd9a107dfcbfbaaf71ece9d
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-112821-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,15313 @@
+2016-08-24 11:28:21,898 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 11:28:21,899 INFO: Info: Labels used: No, Yes
+2016-08-24 11:28:21,899 INFO: Info: Length of dataset:347
+2016-08-24 11:28:21,900 INFO: ### Main Programm for Multiview Classification
+2016-08-24 11:28:21,900 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 11:28:21,901 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 11:28:21,901 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 11:28:21,902 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 11:28:21,902 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 11:28:21,902 INFO: Done: Read Database Files
+2016-08-24 11:28:21,902 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 11:28:21,906 INFO: Done: Determine validation split
+2016-08-24 11:28:21,906 INFO: Start: Determine 2 folds
+2016-08-24 11:28:21,916 INFO: Info: Length of Learning Sets: 122
+2016-08-24 11:28:21,916 INFO: Info: Length of Testing Sets: 122
+2016-08-24 11:28:21,916 INFO: Info: Length of Validation Set: 103
+2016-08-24 11:28:21,916 INFO: Done: Determine folds
+2016-08-24 11:28:21,917 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 11:28:21,917 INFO: Start: Fold number 1
+2016-08-24 11:28:23,496 DEBUG: Start: Iteration 1
+2016-08-24 11:28:23,512 DEBUG: View 0 : 0.612903225806
+2016-08-24 11:28:23,520 DEBUG: View 1 : 0.387096774194
+2016-08-24 11:28:23,602 DEBUG: View 2 : 0.535483870968
+2016-08-24 11:28:23,609 DEBUG: View 3 : 0.612903225806
+2016-08-24 11:28:23,651 DEBUG: Best view : Methyl_
+2016-08-24 11:28:23,726 DEBUG: Start: Iteration 2
+2016-08-24 11:28:23,743 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:28:23,750 DEBUG: View 1 : 0.651612903226
+2016-08-24 11:28:23,835 DEBUG: View 2 : 0.638709677419
+2016-08-24 11:28:23,842 DEBUG: View 3 : 0.606451612903
+2016-08-24 11:28:23,893 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:24,028 DEBUG: Start: Iteration 3
+2016-08-24 11:28:24,045 DEBUG: View 0 : 0.522580645161
+2016-08-24 11:28:24,052 DEBUG: View 1 : 0.374193548387
+2016-08-24 11:28:24,136 DEBUG: View 2 : 0.593548387097
+2016-08-24 11:28:24,143 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:28:24,196 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:24,408 DEBUG: Start: Iteration 4
+2016-08-24 11:28:24,425 DEBUG: View 0 : 0.716129032258
+2016-08-24 11:28:24,432 DEBUG: View 1 : 0.451612903226
+2016-08-24 11:28:24,522 DEBUG: View 2 : 0.535483870968
+2016-08-24 11:28:24,529 DEBUG: View 3 : 0.664516129032
+2016-08-24 11:28:24,584 DEBUG: Best view : Methyl_
+2016-08-24 11:28:24,852 DEBUG: Start: Iteration 5
+2016-08-24 11:28:24,869 DEBUG: View 0 : 0.477419354839
+2016-08-24 11:28:24,876 DEBUG: View 1 : 0.516129032258
+2016-08-24 11:28:24,963 DEBUG: View 2 : 0.548387096774
+2016-08-24 11:28:24,970 DEBUG: View 3 : 0.561290322581
+2016-08-24 11:28:25,026 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:25,368 DEBUG: Start: Iteration 6
+2016-08-24 11:28:25,384 DEBUG: View 0 : 0.535483870968
+2016-08-24 11:28:25,391 DEBUG: View 1 : 0.606451612903
+2016-08-24 11:28:25,478 DEBUG: View 2 : 0.612903225806
+2016-08-24 11:28:25,486 DEBUG: View 3 : 0.522580645161
+2016-08-24 11:28:25,545 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:25,960 DEBUG: Start: Iteration 7
+2016-08-24 11:28:25,978 DEBUG: View 0 : 0.574193548387
+2016-08-24 11:28:25,986 DEBUG: View 1 : 0.406451612903
+2016-08-24 11:28:26,082 DEBUG: View 2 : 0.612903225806
+2016-08-24 11:28:26,090 DEBUG: View 3 : 0.503225806452
+2016-08-24 11:28:26,151 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:26,626 DEBUG: Start: Iteration 8
+2016-08-24 11:28:26,642 DEBUG: View 0 : 0.522580645161
+2016-08-24 11:28:26,649 DEBUG: View 1 : 0.451612903226
+2016-08-24 11:28:26,737 DEBUG: View 2 : 0.529032258065
+2016-08-24 11:28:26,744 DEBUG: View 3 : 0.632258064516
+2016-08-24 11:28:26,806 DEBUG: Best view : Clinic_
+2016-08-24 11:28:27,336 DEBUG: Start: Iteration 9
+2016-08-24 11:28:27,352 DEBUG: View 0 : 0.509677419355
+2016-08-24 11:28:27,360 DEBUG: View 1 : 0.522580645161
+2016-08-24 11:28:27,449 DEBUG: View 2 : 0.632258064516
+2016-08-24 11:28:27,457 DEBUG: View 3 : 0.58064516129
+2016-08-24 11:28:27,521 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:28,127 DEBUG: Start: Iteration 10
+2016-08-24 11:28:28,145 DEBUG: View 0 : 0.483870967742
+2016-08-24 11:28:28,154 DEBUG: View 1 : 0.658064516129
+2016-08-24 11:28:28,254 DEBUG: View 2 : 0.612903225806
+2016-08-24 11:28:28,261 DEBUG: View 3 : 0.664516129032
+2016-08-24 11:28:28,331 DEBUG: Best view : Clinic_
+2016-08-24 11:28:28,997 DEBUG: Start: Iteration 11
+2016-08-24 11:28:29,013 DEBUG: View 0 : 0.574193548387
+2016-08-24 11:28:29,020 DEBUG: View 1 : 0.425806451613
+2016-08-24 11:28:29,110 DEBUG: View 2 : 0.535483870968
+2016-08-24 11:28:29,117 DEBUG: View 3 : 0.703225806452
+2016-08-24 11:28:29,188 DEBUG: Best view : Clinic_
+2016-08-24 11:28:29,912 DEBUG: Start: Iteration 12
+2016-08-24 11:28:29,928 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:28:29,935 DEBUG: View 1 : 0.6
+2016-08-24 11:28:30,025 DEBUG: View 2 : 0.574193548387
+2016-08-24 11:28:30,032 DEBUG: View 3 : 0.574193548387
+2016-08-24 11:28:30,104 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:30,883 DEBUG: Start: Iteration 13
+2016-08-24 11:28:30,899 DEBUG: View 0 : 0.593548387097
+2016-08-24 11:28:30,906 DEBUG: View 1 : 0.690322580645
+2016-08-24 11:28:30,992 DEBUG: View 2 : 0.625806451613
+2016-08-24 11:28:31,000 DEBUG: View 3 : 0.612903225806
+2016-08-24 11:28:31,073 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:31,913 DEBUG: Start: Iteration 14
+2016-08-24 11:28:31,929 DEBUG: View 0 : 0.367741935484
+2016-08-24 11:28:31,937 DEBUG: View 1 : 0.748387096774
+2016-08-24 11:28:32,026 DEBUG: View 2 : 0.548387096774
+2016-08-24 11:28:32,034 DEBUG: View 3 : 0.58064516129
+2016-08-24 11:28:32,109 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:33,005 DEBUG: Start: Iteration 15
+2016-08-24 11:28:33,022 DEBUG: View 0 : 0.587096774194
+2016-08-24 11:28:33,030 DEBUG: View 1 : 0.61935483871
+2016-08-24 11:28:33,117 DEBUG: View 2 : 0.645161290323
+2016-08-24 11:28:33,124 DEBUG: View 3 : 0.529032258065
+2016-08-24 11:28:33,204 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:34,201 DEBUG: Start: Iteration 16
+2016-08-24 11:28:34,217 DEBUG: View 0 : 0.561290322581
+2016-08-24 11:28:34,225 DEBUG: View 1 : 0.593548387097
+2016-08-24 11:28:34,309 DEBUG: View 2 : 0.483870967742
+2016-08-24 11:28:34,317 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:28:34,396 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:35,410 DEBUG: Start: Iteration 17
+2016-08-24 11:28:35,426 DEBUG: View 0 : 0.393548387097
+2016-08-24 11:28:35,434 DEBUG: View 1 : 0.606451612903
+2016-08-24 11:28:35,523 DEBUG: View 2 : 0.535483870968
+2016-08-24 11:28:35,531 DEBUG: View 3 : 0.645161290323
+2016-08-24 11:28:35,625 DEBUG: Best view : Clinic_
+2016-08-24 11:28:36,717 DEBUG: Start: Iteration 18
+2016-08-24 11:28:36,733 DEBUG: View 0 : 0.593548387097
+2016-08-24 11:28:36,741 DEBUG: View 1 : 0.722580645161
+2016-08-24 11:28:36,818 DEBUG: View 2 : 0.490322580645
+2016-08-24 11:28:36,826 DEBUG: View 3 : 0.554838709677
+2016-08-24 11:28:36,912 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:38,050 DEBUG: Start: Iteration 19
+2016-08-24 11:28:38,066 DEBUG: View 0 : 0.522580645161
+2016-08-24 11:28:38,073 DEBUG: View 1 : 0.670967741935
+2016-08-24 11:28:38,158 DEBUG: View 2 : 0.645161290323
+2016-08-24 11:28:38,165 DEBUG: View 3 : 0.561290322581
+2016-08-24 11:28:38,252 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:39,447 DEBUG: Start: Iteration 20
+2016-08-24 11:28:39,463 DEBUG: View 0 : 0.451612903226
+2016-08-24 11:28:39,471 DEBUG: View 1 : 0.554838709677
+2016-08-24 11:28:39,555 DEBUG: View 2 : 0.458064516129
+2016-08-24 11:28:39,563 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:28:39,654 DEBUG: Best view : Clinic_
+2016-08-24 11:28:40,935 DEBUG: Start: Iteration 21
+2016-08-24 11:28:40,951 DEBUG: View 0 : 0.470967741935
+2016-08-24 11:28:40,959 DEBUG: View 1 : 0.374193548387
+2016-08-24 11:28:41,040 DEBUG: View 2 : 0.574193548387
+2016-08-24 11:28:41,047 DEBUG: View 3 : 0.548387096774
+2016-08-24 11:28:41,139 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:42,447 DEBUG: Start: Iteration 22
+2016-08-24 11:28:42,463 DEBUG: View 0 : 0.509677419355
+2016-08-24 11:28:42,471 DEBUG: View 1 : 0.367741935484
+2016-08-24 11:28:42,555 DEBUG: View 2 : 0.593548387097
+2016-08-24 11:28:42,562 DEBUG: View 3 : 0.516129032258
+2016-08-24 11:28:42,655 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:44,058 DEBUG: Start: Iteration 23
+2016-08-24 11:28:44,075 DEBUG: View 0 : 0.483870967742
+2016-08-24 11:28:44,083 DEBUG: View 1 : 0.651612903226
+2016-08-24 11:28:44,169 DEBUG: View 2 : 0.451612903226
+2016-08-24 11:28:44,177 DEBUG: View 3 : 0.529032258065
+2016-08-24 11:28:44,273 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:45,721 DEBUG: Start: Iteration 24
+2016-08-24 11:28:45,737 DEBUG: View 0 : 0.548387096774
+2016-08-24 11:28:45,744 DEBUG: View 1 : 0.645161290323
+2016-08-24 11:28:45,834 DEBUG: View 2 : 0.61935483871
+2016-08-24 11:28:45,842 DEBUG: View 3 : 0.574193548387
+2016-08-24 11:28:45,941 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:47,449 DEBUG: Start: Iteration 25
+2016-08-24 11:28:47,465 DEBUG: View 0 : 0.445161290323
+2016-08-24 11:28:47,473 DEBUG: View 1 : 0.78064516129
+2016-08-24 11:28:47,558 DEBUG: View 2 : 0.464516129032
+2016-08-24 11:28:47,565 DEBUG: View 3 : 0.593548387097
+2016-08-24 11:28:47,664 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:49,222 DEBUG: Start: Iteration 26
+2016-08-24 11:28:49,238 DEBUG: View 0 : 0.458064516129
+2016-08-24 11:28:49,246 DEBUG: View 1 : 0.367741935484
+2016-08-24 11:28:49,329 DEBUG: View 2 : 0.625806451613
+2016-08-24 11:28:49,336 DEBUG: View 3 : 0.606451612903
+2016-08-24 11:28:49,437 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:51,077 DEBUG: Start: Iteration 27
+2016-08-24 11:28:51,093 DEBUG: View 0 : 0.561290322581
+2016-08-24 11:28:51,101 DEBUG: View 1 : 0.632258064516
+2016-08-24 11:28:51,190 DEBUG: View 2 : 0.6
+2016-08-24 11:28:51,198 DEBUG: View 3 : 0.548387096774
+2016-08-24 11:28:51,304 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:53,003 DEBUG: Start: Iteration 28
+2016-08-24 11:28:53,020 DEBUG: View 0 : 0.432258064516
+2016-08-24 11:28:53,027 DEBUG: View 1 : 0.516129032258
+2016-08-24 11:28:53,119 DEBUG: View 2 : 0.670967741935
+2016-08-24 11:28:53,127 DEBUG: View 3 : 0.574193548387
+2016-08-24 11:28:53,232 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:55,010 DEBUG: Start: Iteration 29
+2016-08-24 11:28:55,026 DEBUG: View 0 : 0.541935483871
+2016-08-24 11:28:55,034 DEBUG: View 1 : 0.61935483871
+2016-08-24 11:28:55,121 DEBUG: View 2 : 0.6
+2016-08-24 11:28:55,129 DEBUG: View 3 : 0.529032258065
+2016-08-24 11:28:55,237 DEBUG: Best view : MiRNA__
+2016-08-24 11:28:57,054 DEBUG: Start: Iteration 30
+2016-08-24 11:28:57,070 DEBUG: View 0 : 0.483870967742
+2016-08-24 11:28:57,077 DEBUG: View 1 : 0.612903225806
+2016-08-24 11:28:57,163 DEBUG: View 2 : 0.61935483871
+2016-08-24 11:28:57,171 DEBUG: View 3 : 0.548387096774
+2016-08-24 11:28:57,280 DEBUG: Best view : RANSeq_
+2016-08-24 11:28:59,182 DEBUG: Start: Iteration 31
+2016-08-24 11:28:59,199 DEBUG: View 0 : 0.477419354839
+2016-08-24 11:28:59,206 DEBUG: View 1 : 0.309677419355
+2016-08-24 11:28:59,297 DEBUG: View 2 : 0.696774193548
+2016-08-24 11:28:59,305 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:28:59,417 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:01,454 DEBUG: Start: Iteration 32
+2016-08-24 11:29:01,470 DEBUG: View 0 : 0.464516129032
+2016-08-24 11:29:01,478 DEBUG: View 1 : 0.612903225806
+2016-08-24 11:29:01,566 DEBUG: View 2 : 0.6
+2016-08-24 11:29:01,574 DEBUG: View 3 : 0.664516129032
+2016-08-24 11:29:01,689 DEBUG: Best view : Clinic_
+2016-08-24 11:29:03,714 DEBUG: Start: Iteration 33
+2016-08-24 11:29:03,731 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:29:03,738 DEBUG: View 1 : 0.425806451613
+2016-08-24 11:29:03,820 DEBUG: View 2 : 0.567741935484
+2016-08-24 11:29:03,828 DEBUG: View 3 : 0.548387096774
+2016-08-24 11:29:03,944 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:06,096 DEBUG: Start: Iteration 34
+2016-08-24 11:29:06,113 DEBUG: View 0 : 0.464516129032
+2016-08-24 11:29:06,120 DEBUG: View 1 : 0.425806451613
+2016-08-24 11:29:06,208 DEBUG: View 2 : 0.658064516129
+2016-08-24 11:29:06,216 DEBUG: View 3 : 0.593548387097
+2016-08-24 11:29:06,335 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:08,524 DEBUG: Start: Iteration 35
+2016-08-24 11:29:08,541 DEBUG: View 0 : 0.490322580645
+2016-08-24 11:29:08,549 DEBUG: View 1 : 0.690322580645
+2016-08-24 11:29:08,633 DEBUG: View 2 : 0.606451612903
+2016-08-24 11:29:08,640 DEBUG: View 3 : 0.574193548387
+2016-08-24 11:29:08,763 DEBUG: Best view : MiRNA__
+2016-08-24 11:29:11,058 DEBUG: Start: Iteration 36
+2016-08-24 11:29:11,074 DEBUG: View 0 : 0.6
+2016-08-24 11:29:11,082 DEBUG: View 1 : 0.696774193548
+2016-08-24 11:29:11,172 DEBUG: View 2 : 0.612903225806
+2016-08-24 11:29:11,180 DEBUG: View 3 : 0.561290322581
+2016-08-24 11:29:11,304 DEBUG: Best view : MiRNA__
+2016-08-24 11:29:13,640 DEBUG: Start: Iteration 37
+2016-08-24 11:29:13,658 DEBUG: View 0 : 0.406451612903
+2016-08-24 11:29:13,666 DEBUG: View 1 : 0.703225806452
+2016-08-24 11:29:13,752 DEBUG: View 2 : 0.477419354839
+2016-08-24 11:29:13,760 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:29:13,893 DEBUG: Best view : MiRNA__
+2016-08-24 11:29:16,252 DEBUG: Start: Iteration 38
+2016-08-24 11:29:16,268 DEBUG: View 0 : 0.522580645161
+2016-08-24 11:29:16,276 DEBUG: View 1 : 0.664516129032
+2016-08-24 11:29:16,361 DEBUG: View 2 : 0.625806451613
+2016-08-24 11:29:16,368 DEBUG: View 3 : 0.470967741935
+2016-08-24 11:29:16,496 DEBUG: Best view : MiRNA__
+2016-08-24 11:29:18,908 DEBUG: Start: Iteration 39
+2016-08-24 11:29:18,925 DEBUG: View 0 : 0.432258064516
+2016-08-24 11:29:18,933 DEBUG: View 1 : 0.387096774194
+2016-08-24 11:29:19,021 DEBUG: View 2 : 0.561290322581
+2016-08-24 11:29:19,028 DEBUG: View 3 : 0.529032258065
+2016-08-24 11:29:19,157 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:21,647 DEBUG: Start: Iteration 40
+2016-08-24 11:29:21,664 DEBUG: View 0 : 0.432258064516
+2016-08-24 11:29:21,672 DEBUG: View 1 : 0.638709677419
+2016-08-24 11:29:21,753 DEBUG: View 2 : 0.574193548387
+2016-08-24 11:29:21,760 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:29:21,893 DEBUG: Best view : Clinic_
+2016-08-24 11:29:24,420 DEBUG: Start: Iteration 41
+2016-08-24 11:29:24,437 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:29:24,444 DEBUG: View 1 : 0.529032258065
+2016-08-24 11:29:24,533 DEBUG: View 2 : 0.567741935484
+2016-08-24 11:29:24,541 DEBUG: View 3 : 0.548387096774
+2016-08-24 11:29:24,674 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:27,267 DEBUG: Start: Iteration 42
+2016-08-24 11:29:27,286 DEBUG: View 0 : 0.6
+2016-08-24 11:29:27,295 DEBUG: View 1 : 0.574193548387
+2016-08-24 11:29:27,398 DEBUG: View 2 : 0.651612903226
+2016-08-24 11:29:27,406 DEBUG: View 3 : 0.587096774194
+2016-08-24 11:29:27,542 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:30,222 DEBUG: Start: Iteration 43
+2016-08-24 11:29:30,239 DEBUG: View 0 : 0.58064516129
+2016-08-24 11:29:30,247 DEBUG: View 1 : 0.632258064516
+2016-08-24 11:29:30,332 DEBUG: View 2 : 0.458064516129
+2016-08-24 11:29:30,340 DEBUG: View 3 : 0.529032258065
+2016-08-24 11:29:30,478 DEBUG: Best view : MiRNA__
+2016-08-24 11:29:33,211 DEBUG: Start: Iteration 44
+2016-08-24 11:29:33,227 DEBUG: View 0 : 0.451612903226
+2016-08-24 11:29:33,235 DEBUG: View 1 : 0.445161290323
+2016-08-24 11:29:33,317 DEBUG: View 2 : 0.606451612903
+2016-08-24 11:29:33,325 DEBUG: View 3 : 0.593548387097
+2016-08-24 11:29:33,463 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:36,284 DEBUG: Start: Iteration 45
+2016-08-24 11:29:36,300 DEBUG: View 0 : 0.587096774194
+2016-08-24 11:29:36,308 DEBUG: View 1 : 0.309677419355
+2016-08-24 11:29:36,388 DEBUG: View 2 : 0.548387096774
+2016-08-24 11:29:36,396 DEBUG: View 3 : 0.658064516129
+2016-08-24 11:29:36,539 DEBUG: Best view : Clinic_
+2016-08-24 11:29:39,404 DEBUG: Start: Iteration 46
+2016-08-24 11:29:39,421 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:29:39,429 DEBUG: View 1 : 0.658064516129
+2016-08-24 11:29:39,515 DEBUG: View 2 : 0.574193548387
+2016-08-24 11:29:39,523 DEBUG: View 3 : 0.651612903226
+2016-08-24 11:29:39,668 DEBUG: Best view : Clinic_
+2016-08-24 11:29:42,602 DEBUG: Start: Iteration 47
+2016-08-24 11:29:42,619 DEBUG: View 0 : 0.677419354839
+2016-08-24 11:29:42,627 DEBUG: View 1 : 0.412903225806
+2016-08-24 11:29:42,714 DEBUG: View 2 : 0.587096774194
+2016-08-24 11:29:42,722 DEBUG: View 3 : 0.522580645161
+2016-08-24 11:29:42,870 DEBUG: Best view : Methyl_
+2016-08-24 11:29:45,843 DEBUG: Start: Iteration 48
+2016-08-24 11:29:45,860 DEBUG: View 0 : 0.696774193548
+2016-08-24 11:29:45,868 DEBUG: View 1 : 0.470967741935
+2016-08-24 11:29:45,957 DEBUG: View 2 : 0.535483870968
+2016-08-24 11:29:45,964 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:29:46,113 DEBUG: Best view : Methyl_
+2016-08-24 11:29:49,139 DEBUG: Start: Iteration 49
+2016-08-24 11:29:49,155 DEBUG: View 0 : 0.458064516129
+2016-08-24 11:29:49,162 DEBUG: View 1 : 0.709677419355
+2016-08-24 11:29:49,245 DEBUG: View 2 : 0.522580645161
+2016-08-24 11:29:49,253 DEBUG: View 3 : 0.483870967742
+2016-08-24 11:29:49,402 DEBUG: Best view : MiRNA__
+2016-08-24 11:29:52,569 DEBUG: Start: Iteration 50
+2016-08-24 11:29:52,586 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:29:52,593 DEBUG: View 1 : 0.483870967742
+2016-08-24 11:29:52,683 DEBUG: View 2 : 0.632258064516
+2016-08-24 11:29:52,690 DEBUG: View 3 : 0.561290322581
+2016-08-24 11:29:52,844 DEBUG: Best view : RANSeq_
+2016-08-24 11:29:56,008 DEBUG: Start: Iteration 51
+2016-08-24 11:29:56,024 DEBUG: View 0 : 0.451612903226
+2016-08-24 11:29:56,032 DEBUG: View 1 : 0.464516129032
+2016-08-24 11:29:56,114 DEBUG: View 2 : 0.6
+2016-08-24 11:29:56,121 DEBUG: View 3 : 0.606451612903
+2016-08-24 11:29:56,275 DEBUG: Best view : Clinic_
+2016-08-24 11:29:59,511 DEBUG: Start: Iteration 52
+2016-08-24 11:29:59,528 DEBUG: View 0 : 0.438709677419
+2016-08-24 11:29:59,536 DEBUG: View 1 : 0.341935483871
+2016-08-24 11:29:59,622 DEBUG: View 2 : 0.541935483871
+2016-08-24 11:29:59,630 DEBUG: View 3 : 0.6
+2016-08-24 11:29:59,790 DEBUG: Best view : Clinic_
+2016-08-24 11:30:03,108 DEBUG: Start: Iteration 53
+2016-08-24 11:30:03,124 DEBUG: View 0 : 0.535483870968
+2016-08-24 11:30:03,132 DEBUG: View 1 : 0.509677419355
+2016-08-24 11:30:03,214 DEBUG: View 2 : 0.529032258065
+2016-08-24 11:30:03,222 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:30:03,380 DEBUG: Best view : Clinic_
+2016-08-24 11:30:06,727 DEBUG: Start: Iteration 54
+2016-08-24 11:30:06,744 DEBUG: View 0 : 0.709677419355
+2016-08-24 11:30:06,751 DEBUG: View 1 : 0.296774193548
+2016-08-24 11:30:06,839 DEBUG: View 2 : 0.606451612903
+2016-08-24 11:30:06,847 DEBUG: View 3 : 0.606451612903
+2016-08-24 11:30:07,009 DEBUG: Best view : Methyl_
+2016-08-24 11:30:10,403 DEBUG: Start: Iteration 55
+2016-08-24 11:30:10,420 DEBUG: View 0 : 0.58064516129
+2016-08-24 11:30:10,427 DEBUG: View 1 : 0.470967741935
+2016-08-24 11:30:10,505 DEBUG: View 2 : 0.638709677419
+2016-08-24 11:30:10,513 DEBUG: View 3 : 0.574193548387
+2016-08-24 11:30:10,676 DEBUG: Best view : RANSeq_
+2016-08-24 11:30:14,163 DEBUG: Start: Iteration 56
+2016-08-24 11:30:14,180 DEBUG: View 0 : 0.509677419355
+2016-08-24 11:30:14,188 DEBUG: View 1 : 0.58064516129
+2016-08-24 11:30:14,275 DEBUG: View 2 : 0.58064516129
+2016-08-24 11:30:14,282 DEBUG: View 3 : 0.535483870968
+2016-08-24 11:30:14,450 DEBUG: Best view : MiRNA__
+2016-08-24 11:30:17,979 DEBUG: Start: Iteration 57
+2016-08-24 11:30:17,995 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:30:18,003 DEBUG: View 1 : 0.632258064516
+2016-08-24 11:30:18,090 DEBUG: View 2 : 0.61935483871
+2016-08-24 11:30:18,097 DEBUG: View 3 : 0.567741935484
+2016-08-24 11:30:18,264 DEBUG: Best view : RANSeq_
+2016-08-24 11:30:21,936 DEBUG: Start: Iteration 58
+2016-08-24 11:30:21,952 DEBUG: View 0 : 0.477419354839
+2016-08-24 11:30:21,960 DEBUG: View 1 : 0.535483870968
+2016-08-24 11:30:22,050 DEBUG: View 2 : 0.574193548387
+2016-08-24 11:30:22,057 DEBUG: View 3 : 0.567741935484
+2016-08-24 11:30:22,232 DEBUG: Best view : Clinic_
+2016-08-24 11:30:25,881 DEBUG: Start: Iteration 59
+2016-08-24 11:30:25,897 DEBUG: View 0 : 0.561290322581
+2016-08-24 11:30:25,905 DEBUG: View 1 : 0.638709677419
+2016-08-24 11:30:25,992 DEBUG: View 2 : 0.509677419355
+2016-08-24 11:30:25,999 DEBUG: View 3 : 0.58064516129
+2016-08-24 11:30:26,171 DEBUG: Best view : MiRNA__
+2016-08-24 11:30:29,897 DEBUG: Start: Iteration 60
+2016-08-24 11:30:29,913 DEBUG: View 0 : 0.561290322581
+2016-08-24 11:30:29,921 DEBUG: View 1 : 0.683870967742
+2016-08-24 11:30:30,001 DEBUG: View 2 : 0.587096774194
+2016-08-24 11:30:30,009 DEBUG: View 3 : 0.574193548387
+2016-08-24 11:30:30,182 DEBUG: Best view : MiRNA__
+2016-08-24 11:30:33,969 DEBUG: Start: Iteration 61
+2016-08-24 11:30:33,985 DEBUG: View 0 : 0.509677419355
+2016-08-24 11:30:33,992 DEBUG: View 1 : 0.509677419355
+2016-08-24 11:30:34,074 DEBUG: View 2 : 0.606451612903
+2016-08-24 11:30:34,082 DEBUG: View 3 : 0.625806451613
+2016-08-24 11:30:34,259 DEBUG: Best view : Clinic_
+2016-08-24 11:30:38,085 DEBUG: Start: Iteration 62
+2016-08-24 11:30:38,101 DEBUG: View 0 : 0.470967741935
+2016-08-24 11:30:38,109 DEBUG: View 1 : 0.664516129032
+2016-08-24 11:30:38,192 DEBUG: View 2 : 0.58064516129
+2016-08-24 11:30:38,200 DEBUG: View 3 : 0.612903225806
+2016-08-24 11:30:38,380 DEBUG: Best view : MiRNA__
+2016-08-24 11:30:42,275 DEBUG: Start: Iteration 63
+2016-08-24 11:30:42,291 DEBUG: View 0 : 0.412903225806
+2016-08-24 11:30:42,299 DEBUG: View 1 : 0.483870967742
+2016-08-24 11:30:42,383 DEBUG: View 2 : 0.625806451613
+2016-08-24 11:30:42,391 DEBUG: View 3 : 0.58064516129
+2016-08-24 11:30:42,575 DEBUG: Best view : RANSeq_
+2016-08-24 11:30:46,590 DEBUG: Start: Iteration 64
+2016-08-24 11:30:46,606 DEBUG: View 0 : 0.470967741935
+2016-08-24 11:30:46,614 DEBUG: View 1 : 0.509677419355
+2016-08-24 11:30:46,697 DEBUG: View 2 : 0.567741935484
+2016-08-24 11:30:46,705 DEBUG: View 3 : 0.470967741935
+2016-08-24 11:30:46,888 DEBUG: Best view : RANSeq_
+2016-08-24 11:30:50,945 DEBUG: Start: Iteration 65
+2016-08-24 11:30:50,962 DEBUG: View 0 : 0.451612903226
+2016-08-24 11:30:50,970 DEBUG: View 1 : 0.470967741935
+2016-08-24 11:30:51,059 DEBUG: View 2 : 0.670967741935
+2016-08-24 11:30:51,066 DEBUG: View 3 : 0.522580645161
+2016-08-24 11:30:51,256 DEBUG: Best view : RANSeq_
+2016-08-24 11:30:55,362 DEBUG: Start: Iteration 66
+2016-08-24 11:30:55,379 DEBUG: View 0 : 0.464516129032
+2016-08-24 11:30:55,386 DEBUG: View 1 : 0.645161290323
+2016-08-24 11:30:55,475 DEBUG: View 2 : 0.612903225806
+2016-08-24 11:30:55,482 DEBUG: View 3 : 0.664516129032
+2016-08-24 11:30:55,671 DEBUG: Best view : Clinic_
+2016-08-24 11:30:59,825 DEBUG: Start: Iteration 67
+2016-08-24 11:30:59,842 DEBUG: View 0 : 0.438709677419
+2016-08-24 11:30:59,850 DEBUG: View 1 : 0.541935483871
+2016-08-24 11:30:59,940 DEBUG: View 2 : 0.567741935484
+2016-08-24 11:30:59,948 DEBUG: View 3 : 0.664516129032
+2016-08-24 11:31:00,148 DEBUG: Best view : Clinic_
+2016-08-24 11:31:04,865 DEBUG: Start: Iteration 68
+2016-08-24 11:31:04,891 DEBUG: View 0 : 0.425806451613
+2016-08-24 11:31:04,906 DEBUG: View 1 : 0.677419354839
+2016-08-24 11:31:05,061 DEBUG: View 2 : 0.567741935484
+2016-08-24 11:31:05,070 DEBUG: View 3 : 0.664516129032
+2016-08-24 11:31:05,287 DEBUG: Best view : Clinic_
+2016-08-24 11:31:09,748 DEBUG: Start: Iteration 69
+2016-08-24 11:31:09,764 DEBUG: View 0 : 0.477419354839
+2016-08-24 11:31:09,772 DEBUG: View 1 : 0.722580645161
+2016-08-24 11:31:09,851 DEBUG: View 2 : 0.670967741935
+2016-08-24 11:31:09,859 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:31:10,056 DEBUG: Best view : MiRNA__
+2016-08-24 11:31:14,381 DEBUG: Start: Iteration 70
+2016-08-24 11:31:14,397 DEBUG: View 0 : 0.522580645161
+2016-08-24 11:31:14,405 DEBUG: View 1 : 0.638709677419
+2016-08-24 11:31:14,494 DEBUG: View 2 : 0.587096774194
+2016-08-24 11:31:14,502 DEBUG: View 3 : 0.503225806452
+2016-08-24 11:31:14,698 DEBUG: Best view : MiRNA__
+2016-08-24 11:31:19,091 DEBUG: Start: Iteration 71
+2016-08-24 11:31:19,107 DEBUG: View 0 : 0.425806451613
+2016-08-24 11:31:19,114 DEBUG: View 1 : 0.612903225806
+2016-08-24 11:31:19,197 DEBUG: View 2 : 0.567741935484
+2016-08-24 11:31:19,204 DEBUG: View 3 : 0.574193548387
+2016-08-24 11:31:19,401 DEBUG: Best view : MiRNA__
+2016-08-24 11:31:23,780 DEBUG: Start: Iteration 72
+2016-08-24 11:31:23,796 DEBUG: View 0 : 0.645161290323
+2016-08-24 11:31:23,804 DEBUG: View 1 : 0.477419354839
+2016-08-24 11:31:23,885 DEBUG: View 2 : 0.574193548387
+2016-08-24 11:31:23,893 DEBUG: View 3 : 0.561290322581
+2016-08-24 11:31:24,092 DEBUG: Best view : Methyl_
+2016-08-24 11:31:28,523 DEBUG: Start: Iteration 73
+2016-08-24 11:31:28,539 DEBUG: View 0 : 0.483870967742
+2016-08-24 11:31:28,546 DEBUG: View 1 : 0.593548387097
+2016-08-24 11:31:28,627 DEBUG: View 2 : 0.516129032258
+2016-08-24 11:31:28,635 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:31:28,834 DEBUG: Best view : MiRNA__
+2016-08-24 11:31:33,348 DEBUG: Start: Iteration 74
+2016-08-24 11:31:33,364 DEBUG: View 0 : 0.548387096774
+2016-08-24 11:31:33,372 DEBUG: View 1 : 0.277419354839
+2016-08-24 11:31:33,458 DEBUG: View 2 : 0.645161290323
+2016-08-24 11:31:33,465 DEBUG: View 3 : 0.477419354839
+2016-08-24 11:31:33,668 DEBUG: Best view : RANSeq_
+2016-08-24 11:31:38,258 DEBUG: Start: Iteration 75
+2016-08-24 11:31:38,274 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:31:38,282 DEBUG: View 1 : 0.625806451613
+2016-08-24 11:31:38,355 DEBUG: View 2 : 0.61935483871
+2016-08-24 11:31:38,363 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:31:38,568 DEBUG: Best view : RANSeq_
+2016-08-24 11:31:43,214 DEBUG: Start: Iteration 76
+2016-08-24 11:31:43,230 DEBUG: View 0 : 0.58064516129
+2016-08-24 11:31:43,237 DEBUG: View 1 : 0.606451612903
+2016-08-24 11:31:43,323 DEBUG: View 2 : 0.612903225806
+2016-08-24 11:31:43,331 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:31:43,535 DEBUG: Best view : Clinic_
+2016-08-24 11:31:48,374 DEBUG: Start: Iteration 77
+2016-08-24 11:31:48,393 DEBUG: View 0 : 0.451612903226
+2016-08-24 11:31:48,401 DEBUG: View 1 : 0.690322580645
+2016-08-24 11:31:48,503 DEBUG: View 2 : 0.6
+2016-08-24 11:31:48,512 DEBUG: View 3 : 0.548387096774
+2016-08-24 11:31:48,755 DEBUG: Best view : MiRNA__
+2016-08-24 11:31:53,654 DEBUG: Start: Iteration 78
+2016-08-24 11:31:53,671 DEBUG: View 0 : 0.593548387097
+2016-08-24 11:31:53,678 DEBUG: View 1 : 0.632258064516
+2016-08-24 11:31:53,760 DEBUG: View 2 : 0.612903225806
+2016-08-24 11:31:53,767 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:31:53,976 DEBUG: Best view : MiRNA__
+2016-08-24 11:31:58,943 DEBUG: Start: Iteration 79
+2016-08-24 11:31:58,960 DEBUG: View 0 : 0.503225806452
+2016-08-24 11:31:58,967 DEBUG: View 1 : 0.458064516129
+2016-08-24 11:31:59,055 DEBUG: View 2 : 0.632258064516
+2016-08-24 11:31:59,063 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:31:59,276 DEBUG: Best view : RANSeq_
+2016-08-24 11:32:04,163 DEBUG: Start: Iteration 80
+2016-08-24 11:32:04,180 DEBUG: View 0 : 0.529032258065
+2016-08-24 11:32:04,187 DEBUG: View 1 : 0.361290322581
+2016-08-24 11:32:04,275 DEBUG: View 2 : 0.645161290323
+2016-08-24 11:32:04,283 DEBUG: View 3 : 0.522580645161
+2016-08-24 11:32:04,495 DEBUG: Best view : RANSeq_
+2016-08-24 11:32:09,481 DEBUG: Start: Iteration 81
+2016-08-24 11:32:09,498 DEBUG: View 0 : 0.541935483871
+2016-08-24 11:32:09,506 DEBUG: View 1 : 0.374193548387
+2016-08-24 11:32:09,589 DEBUG: View 2 : 0.593548387097
+2016-08-24 11:32:09,596 DEBUG: View 3 : 0.587096774194
+2016-08-24 11:32:09,813 DEBUG: Best view : Clinic_
+2016-08-24 11:32:14,844 DEBUG: Start: Iteration 82
+2016-08-24 11:32:14,860 DEBUG: View 0 : 0.445161290323
+2016-08-24 11:32:14,868 DEBUG: View 1 : 0.503225806452
+2016-08-24 11:32:14,955 DEBUG: View 2 : 0.490322580645
+2016-08-24 11:32:14,962 DEBUG: View 3 : 0.6
+2016-08-24 11:32:15,180 DEBUG: Best view : Clinic_
+2016-08-24 11:32:20,296 DEBUG: Start: Iteration 83
+2016-08-24 11:32:20,314 DEBUG: View 0 : 0.574193548387
+2016-08-24 11:32:20,322 DEBUG: View 1 : 0.367741935484
+2016-08-24 11:32:20,411 DEBUG: View 2 : 0.625806451613
+2016-08-24 11:32:20,419 DEBUG: View 3 : 0.535483870968
+2016-08-24 11:32:20,648 DEBUG: Best view : RANSeq_
+2016-08-24 11:32:25,914 DEBUG: Start: Iteration 84
+2016-08-24 11:32:25,931 DEBUG: View 0 : 0.509677419355
+2016-08-24 11:32:25,939 DEBUG: View 1 : 0.554838709677
+2016-08-24 11:32:26,026 DEBUG: View 2 : 0.645161290323
+2016-08-24 11:32:26,034 DEBUG: View 3 : 0.612903225806
+2016-08-24 11:32:26,264 DEBUG: Best view : RANSeq_
+2016-08-24 11:32:31,908 DEBUG: Start: Iteration 85
+2016-08-24 11:32:31,927 DEBUG: View 0 : 0.541935483871
+2016-08-24 11:32:31,936 DEBUG: View 1 : 0.509677419355
+2016-08-24 11:32:32,032 DEBUG: View 2 : 0.490322580645
+2016-08-24 11:32:32,039 DEBUG: View 3 : 0.529032258065
+2016-08-24 11:32:32,270 DEBUG: Best view : Clinic_
+2016-08-24 11:32:37,729 DEBUG: Start: Iteration 86
+2016-08-24 11:32:37,746 DEBUG: View 0 : 0.561290322581
+2016-08-24 11:32:37,753 DEBUG: View 1 : 0.612903225806
+2016-08-24 11:32:37,838 DEBUG: View 2 : 0.58064516129
+2016-08-24 11:32:37,845 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:32:38,074 DEBUG: Best view : Clinic_
+2016-08-24 11:32:43,440 DEBUG: Start: Iteration 87
+2016-08-24 11:32:43,456 DEBUG: View 0 : 0.587096774194
+2016-08-24 11:32:43,464 DEBUG: View 1 : 0.490322580645
+2016-08-24 11:32:43,550 DEBUG: View 2 : 0.529032258065
+2016-08-24 11:32:43,558 DEBUG: View 3 : 0.606451612903
+2016-08-24 11:32:43,788 DEBUG: Best view : Clinic_
+2016-08-24 11:32:49,211 DEBUG: Start: Iteration 88
+2016-08-24 11:32:49,227 DEBUG: View 0 : 0.651612903226
+2016-08-24 11:32:49,235 DEBUG: View 1 : 0.483870967742
+2016-08-24 11:32:49,320 DEBUG: View 2 : 0.593548387097
+2016-08-24 11:32:49,327 DEBUG: View 3 : 0.625806451613
+2016-08-24 11:32:49,559 DEBUG: Best view : Methyl_
+2016-08-24 11:32:55,079 DEBUG: Start: Iteration 89
+2016-08-24 11:32:55,096 DEBUG: View 0 : 0.374193548387
+2016-08-24 11:32:55,104 DEBUG: View 1 : 0.625806451613
+2016-08-24 11:32:55,192 DEBUG: View 2 : 0.425806451613
+2016-08-24 11:32:55,199 DEBUG: View 3 : 0.61935483871
+2016-08-24 11:32:55,438 DEBUG: Best view : Clinic_
+2016-08-24 11:33:01,001 DEBUG: Start: Iteration 90
+2016-08-24 11:33:01,018 DEBUG: View 0 : 0.470967741935
+2016-08-24 11:33:01,025 DEBUG: View 1 : 0.683870967742
+2016-08-24 11:33:01,113 DEBUG: View 2 : 0.567741935484
+2016-08-24 11:33:01,120 DEBUG: View 3 : 0.529032258065
+2016-08-24 11:33:01,356 DEBUG: Best view : MiRNA__
+2016-08-24 11:33:06,992 DEBUG: Start: Iteration 91
+2016-08-24 11:33:07,008 DEBUG: View 0 : 0.606451612903
+2016-08-24 11:33:07,016 DEBUG: View 1 : 0.625806451613
+2016-08-24 11:33:07,101 DEBUG: View 2 : 0.587096774194
+2016-08-24 11:33:07,109 DEBUG: View 3 : 0.606451612903
+2016-08-24 11:33:07,353 DEBUG: Best view : Clinic_
+2016-08-24 11:33:13,195 DEBUG: Start: Iteration 92
+2016-08-24 11:33:13,212 DEBUG: View 0 : 0.425806451613
+2016-08-24 11:33:13,219 DEBUG: View 1 : 0.348387096774
+2016-08-24 11:33:13,311 DEBUG: View 2 : 0.529032258065
+2016-08-24 11:33:13,318 DEBUG: View 3 : 0.587096774194
+2016-08-24 11:33:13,560 DEBUG: Best view : Clinic_
+2016-08-24 11:33:19,527 DEBUG: Start: Iteration 93
+2016-08-24 11:33:19,543 DEBUG: View 0 : 0.496774193548
+2016-08-24 11:33:19,551 DEBUG: View 1 : 0.612903225806
+2016-08-24 11:33:19,634 DEBUG: View 2 : 0.58064516129
+2016-08-24 11:33:19,641 DEBUG: View 3 : 0.554838709677
+2016-08-24 11:33:19,896 DEBUG: Best view : MiRNA__
+2016-08-24 11:33:25,762 DEBUG: Start: Iteration 94
+2016-08-24 11:33:25,778 DEBUG: View 0 : 0.445161290323
+2016-08-24 11:33:25,786 DEBUG: View 1 : 0.632258064516
+2016-08-24 11:33:25,869 DEBUG: View 2 : 0.574193548387
+2016-08-24 11:33:25,876 DEBUG: View 3 : 0.522580645161
+2016-08-24 11:33:26,123 DEBUG: Best view : MiRNA__
+2016-08-24 11:33:32,162 DEBUG: Start: Iteration 95
+2016-08-24 11:33:32,179 DEBUG: View 0 : 0.458064516129
+2016-08-24 11:33:32,187 DEBUG: View 1 : 0.638709677419
+2016-08-24 11:33:32,281 DEBUG: View 2 : 0.561290322581
+2016-08-24 11:33:32,288 DEBUG: View 3 : 0.6
+2016-08-24 11:33:32,548 DEBUG: Best view : Clinic_
+2016-08-24 11:33:38,564 DEBUG: Start: Iteration 96
+2016-08-24 11:33:38,581 DEBUG: View 0 : 0.574193548387
+2016-08-24 11:33:38,588 DEBUG: View 1 : 0.367741935484
+2016-08-24 11:33:38,674 DEBUG: View 2 : 0.645161290323
+2016-08-24 11:33:38,681 DEBUG: View 3 : 0.670967741935
+2016-08-24 11:33:38,933 DEBUG: Best view : Clinic_
+2016-08-24 11:33:45,058 DEBUG: Start: Iteration 97
+2016-08-24 11:33:45,076 DEBUG: View 0 : 0.61935483871
+2016-08-24 11:33:45,084 DEBUG: View 1 : 0.658064516129
+2016-08-24 11:33:45,175 DEBUG: View 2 : 0.593548387097
+2016-08-24 11:33:45,182 DEBUG: View 3 : 0.541935483871
+2016-08-24 11:33:45,439 DEBUG: Best view : MiRNA__
+2016-08-24 11:33:51,666 DEBUG: Start: Iteration 98
+2016-08-24 11:33:51,683 DEBUG: View 0 : 0.477419354839
+2016-08-24 11:33:51,691 DEBUG: View 1 : 0.587096774194
+2016-08-24 11:33:51,786 DEBUG: View 2 : 0.548387096774
+2016-08-24 11:33:51,794 DEBUG: View 3 : 0.638709677419
+2016-08-24 11:33:52,065 DEBUG: Best view : Clinic_
+2016-08-24 11:33:58,218 DEBUG: Start: Iteration 99
+2016-08-24 11:33:58,235 DEBUG: View 0 : 0.464516129032
+2016-08-24 11:33:58,243 DEBUG: View 1 : 0.470967741935
+2016-08-24 11:33:58,334 DEBUG: View 2 : 0.554838709677
+2016-08-24 11:33:58,342 DEBUG: View 3 : 0.567741935484
+2016-08-24 11:33:58,600 DEBUG: Best view : Clinic_
+2016-08-24 11:34:04,934 DEBUG: Start: Iteration 100
+2016-08-24 11:34:04,950 DEBUG: View 0 : 0.432258064516
+2016-08-24 11:34:04,957 DEBUG: View 1 : 0.412903225806
+2016-08-24 11:34:05,039 DEBUG: View 2 : 0.561290322581
+2016-08-24 11:34:05,047 DEBUG: View 3 : 0.670967741935
+2016-08-24 11:34:05,308 DEBUG: Best view : Clinic_
+2016-08-24 11:34:11,557 DEBUG: Start: Iteration 101
+2016-08-24 11:34:11,573 DEBUG: View 0 : 0.548387096774
+2016-08-24 11:34:11,580 DEBUG: View 1 : 0.387096774194
+2016-08-24 11:34:11,669 DEBUG: View 2 : 0.541935483871
+2016-08-24 11:34:11,677 DEBUG: View 3 : 0.522580645161
+2016-08-24 11:34:11,937 DEBUG: Best view : Clinic_
+2016-08-24 11:34:18,573 DEBUG: Start: Iteration 102
+2016-08-24 11:34:18,595 DEBUG: View 0 : 0.625806451613
+2016-08-24 11:34:18,604 DEBUG: View 1 : 0.464516129032
+2016-08-24 11:34:18,708 DEBUG: View 2 : 0.606451612903
+2016-08-24 11:34:18,717 DEBUG: View 3 : 0.548387096774
+2016-08-24 11:34:19,004 DEBUG: Best view : Methyl_
+2016-08-24 11:34:25,229 INFO: Start: Classification
+2016-08-24 11:34:40,414 INFO: Done: Fold number 1
+2016-08-24 11:34:40,414 INFO: Start: Fold number 2
+2016-08-24 11:34:42,007 DEBUG: Start: Iteration 1
+2016-08-24 11:34:42,022 DEBUG: View 0 : 0.377358490566
+2016-08-24 11:34:42,029 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:34:42,059 DEBUG: View 2 : 0.377358490566
+2016-08-24 11:34:42,067 DEBUG: View 3 : 0.377358490566
+2016-08-24 11:34:42,108 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:42,178 DEBUG: Start: Iteration 2
+2016-08-24 11:34:42,195 DEBUG: View 0 : 0.465408805031
+2016-08-24 11:34:42,202 DEBUG: View 1 : 0.471698113208
+2016-08-24 11:34:42,289 DEBUG: View 2 : 0.647798742138
+2016-08-24 11:34:42,297 DEBUG: View 3 : 0.477987421384
+2016-08-24 11:34:42,342 DEBUG: Best view : RANSeq_
+2016-08-24 11:34:42,487 DEBUG: Start: Iteration 3
+2016-08-24 11:34:42,504 DEBUG: View 0 : 0.389937106918
+2016-08-24 11:34:42,511 DEBUG: View 1 : 0.553459119497
+2016-08-24 11:34:42,594 DEBUG: View 2 : 0.503144654088
+2016-08-24 11:34:42,602 DEBUG: View 3 : 0.534591194969
+2016-08-24 11:34:42,655 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:42,859 DEBUG: Start: Iteration 4
+2016-08-24 11:34:42,875 DEBUG: View 0 : 0.591194968553
+2016-08-24 11:34:42,883 DEBUG: View 1 : 0.603773584906
+2016-08-24 11:34:42,965 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:34:42,973 DEBUG: View 3 : 0.666666666667
+2016-08-24 11:34:43,029 DEBUG: Best view : Clinic_
+2016-08-24 11:34:43,290 DEBUG: Start: Iteration 5
+2016-08-24 11:34:43,306 DEBUG: View 0 : 0.559748427673
+2016-08-24 11:34:43,314 DEBUG: View 1 : 0.446540880503
+2016-08-24 11:34:43,397 DEBUG: View 2 : 0.547169811321
+2016-08-24 11:34:43,404 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:34:43,461 DEBUG: Best view : Clinic_
+2016-08-24 11:34:43,781 DEBUG: Start: Iteration 6
+2016-08-24 11:34:43,797 DEBUG: View 0 : 0.358490566038
+2016-08-24 11:34:43,805 DEBUG: View 1 : 0.698113207547
+2016-08-24 11:34:43,891 DEBUG: View 2 : 0.509433962264
+2016-08-24 11:34:43,899 DEBUG: View 3 : 0.528301886792
+2016-08-24 11:34:43,958 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:44,334 DEBUG: Start: Iteration 7
+2016-08-24 11:34:44,351 DEBUG: View 0 : 0.503144654088
+2016-08-24 11:34:44,358 DEBUG: View 1 : 0.635220125786
+2016-08-24 11:34:44,445 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:34:44,453 DEBUG: View 3 : 0.660377358491
+2016-08-24 11:34:44,514 DEBUG: Best view : Clinic_
+2016-08-24 11:34:44,948 DEBUG: Start: Iteration 8
+2016-08-24 11:34:44,964 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:34:44,972 DEBUG: View 1 : 0.465408805031
+2016-08-24 11:34:45,055 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:34:45,063 DEBUG: View 3 : 0.647798742138
+2016-08-24 11:34:45,129 DEBUG: Best view : Clinic_
+2016-08-24 11:34:45,620 DEBUG: Start: Iteration 9
+2016-08-24 11:34:45,637 DEBUG: View 0 : 0.553459119497
+2016-08-24 11:34:45,644 DEBUG: View 1 : 0.446540880503
+2016-08-24 11:34:45,730 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:34:45,738 DEBUG: View 3 : 0.553459119497
+2016-08-24 11:34:45,804 DEBUG: Best view : RANSeq_
+2016-08-24 11:34:46,365 DEBUG: Start: Iteration 10
+2016-08-24 11:34:46,382 DEBUG: View 0 : 0.465408805031
+2016-08-24 11:34:46,389 DEBUG: View 1 : 0.465408805031
+2016-08-24 11:34:46,476 DEBUG: View 2 : 0.666666666667
+2016-08-24 11:34:46,484 DEBUG: View 3 : 0.553459119497
+2016-08-24 11:34:46,553 DEBUG: Best view : RANSeq_
+2016-08-24 11:34:47,192 DEBUG: Start: Iteration 11
+2016-08-24 11:34:47,209 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:34:47,216 DEBUG: View 1 : 0.672955974843
+2016-08-24 11:34:47,304 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:34:47,312 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:34:47,384 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:48,078 DEBUG: Start: Iteration 12
+2016-08-24 11:34:48,094 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:34:48,102 DEBUG: View 1 : 0.320754716981
+2016-08-24 11:34:48,193 DEBUG: View 2 : 0.616352201258
+2016-08-24 11:34:48,201 DEBUG: View 3 : 0.522012578616
+2016-08-24 11:34:48,273 DEBUG: Best view : RANSeq_
+2016-08-24 11:34:49,039 DEBUG: Start: Iteration 13
+2016-08-24 11:34:49,055 DEBUG: View 0 : 0.364779874214
+2016-08-24 11:34:49,063 DEBUG: View 1 : 0.641509433962
+2016-08-24 11:34:49,152 DEBUG: View 2 : 0.534591194969
+2016-08-24 11:34:49,159 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:34:49,235 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:50,060 DEBUG: Start: Iteration 14
+2016-08-24 11:34:50,077 DEBUG: View 0 : 0.635220125786
+2016-08-24 11:34:50,084 DEBUG: View 1 : 0.691823899371
+2016-08-24 11:34:50,167 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:34:50,174 DEBUG: View 3 : 0.528301886792
+2016-08-24 11:34:50,253 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:51,136 DEBUG: Start: Iteration 15
+2016-08-24 11:34:51,153 DEBUG: View 0 : 0.427672955975
+2016-08-24 11:34:51,161 DEBUG: View 1 : 0.62893081761
+2016-08-24 11:34:51,245 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:34:51,252 DEBUG: View 3 : 0.616352201258
+2016-08-24 11:34:51,334 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:52,275 DEBUG: Start: Iteration 16
+2016-08-24 11:34:52,292 DEBUG: View 0 : 0.528301886792
+2016-08-24 11:34:52,300 DEBUG: View 1 : 0.672955974843
+2016-08-24 11:34:52,387 DEBUG: View 2 : 0.610062893082
+2016-08-24 11:34:52,395 DEBUG: View 3 : 0.540880503145
+2016-08-24 11:34:52,478 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:53,479 DEBUG: Start: Iteration 17
+2016-08-24 11:34:53,495 DEBUG: View 0 : 0.522012578616
+2016-08-24 11:34:53,503 DEBUG: View 1 : 0.471698113208
+2016-08-24 11:34:53,590 DEBUG: View 2 : 0.654088050314
+2016-08-24 11:34:53,597 DEBUG: View 3 : 0.566037735849
+2016-08-24 11:34:53,682 DEBUG: Best view : RANSeq_
+2016-08-24 11:34:54,747 DEBUG: Start: Iteration 18
+2016-08-24 11:34:54,764 DEBUG: View 0 : 0.522012578616
+2016-08-24 11:34:54,771 DEBUG: View 1 : 0.522012578616
+2016-08-24 11:34:54,855 DEBUG: View 2 : 0.666666666667
+2016-08-24 11:34:54,863 DEBUG: View 3 : 0.528301886792
+2016-08-24 11:34:54,949 DEBUG: Best view : RANSeq_
+2016-08-24 11:34:56,085 DEBUG: Start: Iteration 19
+2016-08-24 11:34:56,101 DEBUG: View 0 : 0.572327044025
+2016-08-24 11:34:56,109 DEBUG: View 1 : 0.616352201258
+2016-08-24 11:34:56,191 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:34:56,198 DEBUG: View 3 : 0.591194968553
+2016-08-24 11:34:56,287 DEBUG: Best view : MiRNA__
+2016-08-24 11:34:57,480 DEBUG: Start: Iteration 20
+2016-08-24 11:34:57,497 DEBUG: View 0 : 0.522012578616
+2016-08-24 11:34:57,504 DEBUG: View 1 : 0.51572327044
+2016-08-24 11:34:57,582 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:34:57,590 DEBUG: View 3 : 0.647798742138
+2016-08-24 11:34:57,681 DEBUG: Best view : Clinic_
+2016-08-24 11:34:58,933 DEBUG: Start: Iteration 21
+2016-08-24 11:34:58,950 DEBUG: View 0 : 0.446540880503
+2016-08-24 11:34:58,958 DEBUG: View 1 : 0.691823899371
+2016-08-24 11:34:59,041 DEBUG: View 2 : 0.48427672956
+2016-08-24 11:34:59,048 DEBUG: View 3 : 0.666666666667
+2016-08-24 11:34:59,141 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:00,451 DEBUG: Start: Iteration 22
+2016-08-24 11:35:00,467 DEBUG: View 0 : 0.559748427673
+2016-08-24 11:35:00,474 DEBUG: View 1 : 0.654088050314
+2016-08-24 11:35:00,561 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:35:00,569 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:35:00,663 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:02,029 DEBUG: Start: Iteration 23
+2016-08-24 11:35:02,046 DEBUG: View 0 : 0.433962264151
+2016-08-24 11:35:02,053 DEBUG: View 1 : 0.616352201258
+2016-08-24 11:35:02,140 DEBUG: View 2 : 0.471698113208
+2016-08-24 11:35:02,147 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:35:02,244 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:03,666 DEBUG: Start: Iteration 24
+2016-08-24 11:35:03,683 DEBUG: View 0 : 0.641509433962
+2016-08-24 11:35:03,690 DEBUG: View 1 : 0.654088050314
+2016-08-24 11:35:03,773 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:35:03,781 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:35:03,880 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:05,362 DEBUG: Start: Iteration 25
+2016-08-24 11:35:05,379 DEBUG: View 0 : 0.616352201258
+2016-08-24 11:35:05,386 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:35:05,465 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:35:05,472 DEBUG: View 3 : 0.666666666667
+2016-08-24 11:35:05,574 DEBUG: Best view : Clinic_
+2016-08-24 11:35:07,114 DEBUG: Start: Iteration 26
+2016-08-24 11:35:07,130 DEBUG: View 0 : 0.377358490566
+2016-08-24 11:35:07,138 DEBUG: View 1 : 0.660377358491
+2016-08-24 11:35:07,224 DEBUG: View 2 : 0.540880503145
+2016-08-24 11:35:07,232 DEBUG: View 3 : 0.654088050314
+2016-08-24 11:35:07,335 DEBUG: Best view : Clinic_
+2016-08-24 11:35:08,934 DEBUG: Start: Iteration 27
+2016-08-24 11:35:08,950 DEBUG: View 0 : 0.446540880503
+2016-08-24 11:35:08,958 DEBUG: View 1 : 0.691823899371
+2016-08-24 11:35:09,044 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:35:09,052 DEBUG: View 3 : 0.566037735849
+2016-08-24 11:35:09,158 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:10,846 DEBUG: Start: Iteration 28
+2016-08-24 11:35:10,863 DEBUG: View 0 : 0.603773584906
+2016-08-24 11:35:10,870 DEBUG: View 1 : 0.51572327044
+2016-08-24 11:35:10,957 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:35:10,964 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:35:11,072 DEBUG: Best view : Clinic_
+2016-08-24 11:35:12,786 DEBUG: Start: Iteration 29
+2016-08-24 11:35:12,803 DEBUG: View 0 : 0.622641509434
+2016-08-24 11:35:12,810 DEBUG: View 1 : 0.729559748428
+2016-08-24 11:35:12,898 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:35:12,905 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:35:13,015 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:14,788 DEBUG: Start: Iteration 30
+2016-08-24 11:35:14,804 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:35:14,812 DEBUG: View 1 : 0.320754716981
+2016-08-24 11:35:14,896 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:35:14,903 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:35:15,016 DEBUG: Best view : Clinic_
+2016-08-24 11:35:16,849 DEBUG: Start: Iteration 31
+2016-08-24 11:35:16,866 DEBUG: View 0 : 0.522012578616
+2016-08-24 11:35:16,874 DEBUG: View 1 : 0.465408805031
+2016-08-24 11:35:16,956 DEBUG: View 2 : 0.654088050314
+2016-08-24 11:35:16,964 DEBUG: View 3 : 0.622641509434
+2016-08-24 11:35:17,078 DEBUG: Best view : RANSeq_
+2016-08-24 11:35:18,980 DEBUG: Start: Iteration 32
+2016-08-24 11:35:18,996 DEBUG: View 0 : 0.59748427673
+2016-08-24 11:35:19,004 DEBUG: View 1 : 0.477987421384
+2016-08-24 11:35:19,090 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:35:19,098 DEBUG: View 3 : 0.528301886792
+2016-08-24 11:35:19,214 DEBUG: Best view : RANSeq_
+2016-08-24 11:35:21,188 DEBUG: Start: Iteration 33
+2016-08-24 11:35:21,204 DEBUG: View 0 : 0.660377358491
+2016-08-24 11:35:21,211 DEBUG: View 1 : 0.566037735849
+2016-08-24 11:35:21,298 DEBUG: View 2 : 0.522012578616
+2016-08-24 11:35:21,306 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:35:21,426 DEBUG: Best view : Methyl_
+2016-08-24 11:35:23,462 DEBUG: Start: Iteration 34
+2016-08-24 11:35:23,478 DEBUG: View 0 : 0.490566037736
+2016-08-24 11:35:23,485 DEBUG: View 1 : 0.345911949686
+2016-08-24 11:35:23,572 DEBUG: View 2 : 0.584905660377
+2016-08-24 11:35:23,580 DEBUG: View 3 : 0.610062893082
+2016-08-24 11:35:23,699 DEBUG: Best view : Clinic_
+2016-08-24 11:35:25,792 DEBUG: Start: Iteration 35
+2016-08-24 11:35:25,809 DEBUG: View 0 : 0.660377358491
+2016-08-24 11:35:25,816 DEBUG: View 1 : 0.528301886792
+2016-08-24 11:35:25,904 DEBUG: View 2 : 0.610062893082
+2016-08-24 11:35:25,912 DEBUG: View 3 : 0.654088050314
+2016-08-24 11:35:26,035 DEBUG: Best view : Clinic_
+2016-08-24 11:35:28,184 DEBUG: Start: Iteration 36
+2016-08-24 11:35:28,201 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:35:28,208 DEBUG: View 1 : 0.62893081761
+2016-08-24 11:35:28,294 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:35:28,302 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:35:28,427 DEBUG: Best view : Clinic_
+2016-08-24 11:35:30,683 DEBUG: Start: Iteration 37
+2016-08-24 11:35:30,700 DEBUG: View 0 : 0.477987421384
+2016-08-24 11:35:30,707 DEBUG: View 1 : 0.471698113208
+2016-08-24 11:35:30,801 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:35:30,809 DEBUG: View 3 : 0.616352201258
+2016-08-24 11:35:30,938 DEBUG: Best view : Clinic_
+2016-08-24 11:35:33,258 DEBUG: Start: Iteration 38
+2016-08-24 11:35:33,274 DEBUG: View 0 : 0.534591194969
+2016-08-24 11:35:33,282 DEBUG: View 1 : 0.748427672956
+2016-08-24 11:35:33,366 DEBUG: View 2 : 0.471698113208
+2016-08-24 11:35:33,374 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:35:33,507 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:35,848 DEBUG: Start: Iteration 39
+2016-08-24 11:35:35,866 DEBUG: View 0 : 0.591194968553
+2016-08-24 11:35:35,875 DEBUG: View 1 : 0.509433962264
+2016-08-24 11:35:35,997 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:35:36,007 DEBUG: View 3 : 0.610062893082
+2016-08-24 11:35:36,153 DEBUG: Best view : Clinic_
+2016-08-24 11:35:38,662 DEBUG: Start: Iteration 40
+2016-08-24 11:35:38,681 DEBUG: View 0 : 0.540880503145
+2016-08-24 11:35:38,689 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:35:38,778 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:35:38,786 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:35:38,925 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:41,412 DEBUG: Start: Iteration 41
+2016-08-24 11:35:41,428 DEBUG: View 0 : 0.534591194969
+2016-08-24 11:35:41,436 DEBUG: View 1 : 0.345911949686
+2016-08-24 11:35:41,516 DEBUG: View 2 : 0.534591194969
+2016-08-24 11:35:41,524 DEBUG: View 3 : 0.534591194969
+2016-08-24 11:35:41,661 DEBUG: Best view : Clinic_
+2016-08-24 11:35:44,288 DEBUG: Start: Iteration 42
+2016-08-24 11:35:44,304 DEBUG: View 0 : 0.452830188679
+2016-08-24 11:35:44,312 DEBUG: View 1 : 0.723270440252
+2016-08-24 11:35:44,399 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:35:44,407 DEBUG: View 3 : 0.729559748428
+2016-08-24 11:35:44,556 DEBUG: Best view : Clinic_
+2016-08-24 11:35:47,232 DEBUG: Start: Iteration 43
+2016-08-24 11:35:47,248 DEBUG: View 0 : 0.610062893082
+2016-08-24 11:35:47,256 DEBUG: View 1 : 0.528301886792
+2016-08-24 11:35:47,339 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:35:47,346 DEBUG: View 3 : 0.591194968553
+2016-08-24 11:35:47,500 DEBUG: Best view : Clinic_
+2016-08-24 11:35:50,194 DEBUG: Start: Iteration 44
+2016-08-24 11:35:50,211 DEBUG: View 0 : 0.540880503145
+2016-08-24 11:35:50,218 DEBUG: View 1 : 0.48427672956
+2016-08-24 11:35:50,308 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:35:50,317 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:35:50,478 DEBUG: Best view : RANSeq_
+2016-08-24 11:35:53,306 DEBUG: Start: Iteration 45
+2016-08-24 11:35:53,322 DEBUG: View 0 : 0.452830188679
+2016-08-24 11:35:53,330 DEBUG: View 1 : 0.641509433962
+2016-08-24 11:35:53,416 DEBUG: View 2 : 0.540880503145
+2016-08-24 11:35:53,424 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:35:53,570 DEBUG: Best view : MiRNA__
+2016-08-24 11:35:56,450 DEBUG: Start: Iteration 46
+2016-08-24 11:35:56,468 DEBUG: View 0 : 0.723270440252
+2016-08-24 11:35:56,476 DEBUG: View 1 : 0.534591194969
+2016-08-24 11:35:56,578 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:35:56,587 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:35:56,742 DEBUG: Best view : Methyl_
+2016-08-24 11:35:59,658 DEBUG: Start: Iteration 47
+2016-08-24 11:35:59,674 DEBUG: View 0 : 0.528301886792
+2016-08-24 11:35:59,682 DEBUG: View 1 : 0.446540880503
+2016-08-24 11:35:59,765 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:35:59,772 DEBUG: View 3 : 0.534591194969
+2016-08-24 11:35:59,924 DEBUG: Best view : RANSeq_
+2016-08-24 11:36:02,916 DEBUG: Start: Iteration 48
+2016-08-24 11:36:02,932 DEBUG: View 0 : 0.40251572327
+2016-08-24 11:36:02,940 DEBUG: View 1 : 0.641509433962
+2016-08-24 11:36:03,023 DEBUG: View 2 : 0.496855345912
+2016-08-24 11:36:03,031 DEBUG: View 3 : 0.459119496855
+2016-08-24 11:36:03,196 DEBUG: Best view : MiRNA__
+2016-08-24 11:36:06,216 DEBUG: Start: Iteration 49
+2016-08-24 11:36:06,232 DEBUG: View 0 : 0.635220125786
+2016-08-24 11:36:06,240 DEBUG: View 1 : 0.314465408805
+2016-08-24 11:36:06,322 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:36:06,330 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:36:06,483 DEBUG: Best view : Methyl_
+2016-08-24 11:36:09,605 DEBUG: Start: Iteration 50
+2016-08-24 11:36:09,622 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:36:09,629 DEBUG: View 1 : 0.51572327044
+2016-08-24 11:36:09,717 DEBUG: View 2 : 0.503144654088
+2016-08-24 11:36:09,725 DEBUG: View 3 : 0.465408805031
+2016-08-24 11:36:09,886 DEBUG: Best view : MiRNA__
+2016-08-24 11:36:13,100 DEBUG: Start: Iteration 51
+2016-08-24 11:36:13,116 DEBUG: View 0 : 0.591194968553
+2016-08-24 11:36:13,124 DEBUG: View 1 : 0.320754716981
+2016-08-24 11:36:13,203 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:36:13,211 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:36:13,377 DEBUG: Best view : Clinic_
+2016-08-24 11:36:16,654 DEBUG: Start: Iteration 52
+2016-08-24 11:36:16,673 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:36:16,682 DEBUG: View 1 : 0.37106918239
+2016-08-24 11:36:16,782 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:36:16,789 DEBUG: View 3 : 0.566037735849
+2016-08-24 11:36:16,950 DEBUG: Best view : RANSeq_
+2016-08-24 11:36:20,173 DEBUG: Start: Iteration 53
+2016-08-24 11:36:20,190 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:36:20,197 DEBUG: View 1 : 0.647798742138
+2016-08-24 11:36:20,293 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:36:20,300 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:36:20,464 DEBUG: Best view : MiRNA__
+2016-08-24 11:36:23,754 DEBUG: Start: Iteration 54
+2016-08-24 11:36:23,770 DEBUG: View 0 : 0.421383647799
+2016-08-24 11:36:23,778 DEBUG: View 1 : 0.566037735849
+2016-08-24 11:36:23,867 DEBUG: View 2 : 0.654088050314
+2016-08-24 11:36:23,875 DEBUG: View 3 : 0.691823899371
+2016-08-24 11:36:24,040 DEBUG: Best view : Clinic_
+2016-08-24 11:36:27,636 DEBUG: Start: Iteration 55
+2016-08-24 11:36:27,653 DEBUG: View 0 : 0.51572327044
+2016-08-24 11:36:27,661 DEBUG: View 1 : 0.320754716981
+2016-08-24 11:36:27,749 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:36:27,756 DEBUG: View 3 : 0.641509433962
+2016-08-24 11:36:27,935 DEBUG: Best view : Clinic_
+2016-08-24 11:36:31,305 DEBUG: Start: Iteration 56
+2016-08-24 11:36:31,322 DEBUG: View 0 : 0.408805031447
+2016-08-24 11:36:31,329 DEBUG: View 1 : 0.452830188679
+2016-08-24 11:36:31,441 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:36:31,448 DEBUG: View 3 : 0.654088050314
+2016-08-24 11:36:31,615 DEBUG: Best view : Clinic_
+2016-08-24 11:36:35,028 DEBUG: Start: Iteration 57
+2016-08-24 11:36:35,044 DEBUG: View 0 : 0.389937106918
+2016-08-24 11:36:35,052 DEBUG: View 1 : 0.364779874214
+2016-08-24 11:36:35,141 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:36:35,148 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:36:35,319 DEBUG: Best view : Clinic_
+2016-08-24 11:36:38,792 DEBUG: Start: Iteration 58
+2016-08-24 11:36:38,808 DEBUG: View 0 : 0.477987421384
+2016-08-24 11:36:38,816 DEBUG: View 1 : 0.522012578616
+2016-08-24 11:36:38,899 DEBUG: View 2 : 0.635220125786
+2016-08-24 11:36:38,906 DEBUG: View 3 : 0.540880503145
+2016-08-24 11:36:39,079 DEBUG: Best view : RANSeq_
+2016-08-24 11:36:42,622 DEBUG: Start: Iteration 59
+2016-08-24 11:36:42,638 DEBUG: View 0 : 0.616352201258
+2016-08-24 11:36:42,645 DEBUG: View 1 : 0.616352201258
+2016-08-24 11:36:42,729 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:36:42,736 DEBUG: View 3 : 0.509433962264
+2016-08-24 11:36:42,910 DEBUG: Best view : MiRNA__
+2016-08-24 11:36:46,544 DEBUG: Start: Iteration 60
+2016-08-24 11:36:46,561 DEBUG: View 0 : 0.503144654088
+2016-08-24 11:36:46,569 DEBUG: View 1 : 0.528301886792
+2016-08-24 11:36:46,659 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:36:46,667 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:36:46,846 DEBUG: Best view : Clinic_
+2016-08-24 11:36:50,629 DEBUG: Start: Iteration 61
+2016-08-24 11:36:50,646 DEBUG: View 0 : 0.59748427673
+2016-08-24 11:36:50,654 DEBUG: View 1 : 0.647798742138
+2016-08-24 11:36:50,744 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:36:50,752 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:36:50,935 DEBUG: Best view : MiRNA__
+2016-08-24 11:36:54,877 DEBUG: Start: Iteration 62
+2016-08-24 11:36:54,895 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:36:54,903 DEBUG: View 1 : 0.786163522013
+2016-08-24 11:36:54,992 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:36:55,000 DEBUG: View 3 : 0.603773584906
+2016-08-24 11:36:55,199 DEBUG: Best view : MiRNA__
+2016-08-24 11:36:59,096 DEBUG: Start: Iteration 63
+2016-08-24 11:36:59,113 DEBUG: View 0 : 0.490566037736
+2016-08-24 11:36:59,121 DEBUG: View 1 : 0.710691823899
+2016-08-24 11:36:59,208 DEBUG: View 2 : 0.534591194969
+2016-08-24 11:36:59,216 DEBUG: View 3 : 0.566037735849
+2016-08-24 11:36:59,403 DEBUG: Best view : MiRNA__
+2016-08-24 11:37:03,332 DEBUG: Start: Iteration 64
+2016-08-24 11:37:03,350 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:37:03,358 DEBUG: View 1 : 0.603773584906
+2016-08-24 11:37:03,443 DEBUG: View 2 : 0.660377358491
+2016-08-24 11:37:03,450 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:37:03,637 DEBUG: Best view : RANSeq_
+2016-08-24 11:37:07,877 DEBUG: Start: Iteration 65
+2016-08-24 11:37:07,893 DEBUG: View 0 : 0.62893081761
+2016-08-24 11:37:07,901 DEBUG: View 1 : 0.37106918239
+2016-08-24 11:37:07,990 DEBUG: View 2 : 0.503144654088
+2016-08-24 11:37:07,998 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:37:08,188 DEBUG: Best view : Methyl_
+2016-08-24 11:37:12,223 DEBUG: Start: Iteration 66
+2016-08-24 11:37:12,239 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:37:12,247 DEBUG: View 1 : 0.440251572327
+2016-08-24 11:37:12,335 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:37:12,343 DEBUG: View 3 : 0.647798742138
+2016-08-24 11:37:12,533 DEBUG: Best view : Clinic_
+2016-08-24 11:37:16,630 DEBUG: Start: Iteration 67
+2016-08-24 11:37:16,646 DEBUG: View 0 : 0.572327044025
+2016-08-24 11:37:16,654 DEBUG: View 1 : 0.559748427673
+2016-08-24 11:37:16,741 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:37:16,749 DEBUG: View 3 : 0.616352201258
+2016-08-24 11:37:16,941 DEBUG: Best view : Clinic_
+2016-08-24 11:37:21,342 DEBUG: Start: Iteration 68
+2016-08-24 11:37:21,359 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:37:21,367 DEBUG: View 1 : 0.48427672956
+2016-08-24 11:37:21,464 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:37:21,472 DEBUG: View 3 : 0.710691823899
+2016-08-24 11:37:21,671 DEBUG: Best view : Clinic_
+2016-08-24 11:37:26,351 DEBUG: Start: Iteration 69
+2016-08-24 11:37:26,368 DEBUG: View 0 : 0.415094339623
+2016-08-24 11:37:26,376 DEBUG: View 1 : 0.603773584906
+2016-08-24 11:37:26,471 DEBUG: View 2 : 0.610062893082
+2016-08-24 11:37:26,479 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:37:26,674 DEBUG: Best view : MiRNA__
+2016-08-24 11:37:30,968 DEBUG: Start: Iteration 70
+2016-08-24 11:37:30,985 DEBUG: View 0 : 0.459119496855
+2016-08-24 11:37:30,993 DEBUG: View 1 : 0.471698113208
+2016-08-24 11:37:31,080 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:37:31,088 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:37:31,289 DEBUG: Best view : RANSeq_
+2016-08-24 11:37:35,887 DEBUG: Start: Iteration 71
+2016-08-24 11:37:35,904 DEBUG: View 0 : 0.672955974843
+2016-08-24 11:37:35,912 DEBUG: View 1 : 0.446540880503
+2016-08-24 11:37:35,999 DEBUG: View 2 : 0.440251572327
+2016-08-24 11:37:36,009 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:37:36,239 DEBUG: Best view : Methyl_
+2016-08-24 11:37:40,827 DEBUG: Start: Iteration 72
+2016-08-24 11:37:40,844 DEBUG: View 0 : 0.446540880503
+2016-08-24 11:37:40,852 DEBUG: View 1 : 0.389937106918
+2016-08-24 11:37:40,935 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:37:40,943 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:37:41,157 DEBUG: Best view : RANSeq_
+2016-08-24 11:37:45,977 DEBUG: Start: Iteration 73
+2016-08-24 11:37:45,997 DEBUG: View 0 : 0.591194968553
+2016-08-24 11:37:46,007 DEBUG: View 1 : 0.610062893082
+2016-08-24 11:37:46,116 DEBUG: View 2 : 0.528301886792
+2016-08-24 11:37:46,124 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:37:46,338 DEBUG: Best view : Clinic_
+2016-08-24 11:37:50,835 DEBUG: Start: Iteration 74
+2016-08-24 11:37:50,851 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:37:50,859 DEBUG: View 1 : 0.40251572327
+2016-08-24 11:37:50,946 DEBUG: View 2 : 0.635220125786
+2016-08-24 11:37:50,955 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:37:51,163 DEBUG: Best view : RANSeq_
+2016-08-24 11:37:55,833 DEBUG: Start: Iteration 75
+2016-08-24 11:37:55,851 DEBUG: View 0 : 0.603773584906
+2016-08-24 11:37:55,859 DEBUG: View 1 : 0.396226415094
+2016-08-24 11:37:55,965 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:37:55,973 DEBUG: View 3 : 0.465408805031
+2016-08-24 11:37:56,187 DEBUG: Best view : Methyl_
+2016-08-24 11:38:01,052 DEBUG: Start: Iteration 76
+2016-08-24 11:38:01,068 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:38:01,076 DEBUG: View 1 : 0.685534591195
+2016-08-24 11:38:01,174 DEBUG: View 2 : 0.490566037736
+2016-08-24 11:38:01,183 DEBUG: View 3 : 0.540880503145
+2016-08-24 11:38:01,400 DEBUG: Best view : MiRNA__
+2016-08-24 11:38:06,415 DEBUG: Start: Iteration 77
+2016-08-24 11:38:06,435 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:38:06,449 DEBUG: View 1 : 0.522012578616
+2016-08-24 11:38:06,570 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:38:06,579 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:38:06,827 DEBUG: Best view : Clinic_
+2016-08-24 11:38:11,928 DEBUG: Start: Iteration 78
+2016-08-24 11:38:11,945 DEBUG: View 0 : 0.471698113208
+2016-08-24 11:38:11,953 DEBUG: View 1 : 0.584905660377
+2016-08-24 11:38:12,052 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:38:12,062 DEBUG: View 3 : 0.622641509434
+2016-08-24 11:38:12,282 DEBUG: Best view : Clinic_
+2016-08-24 11:38:17,220 DEBUG: Start: Iteration 79
+2016-08-24 11:38:17,236 DEBUG: View 0 : 0.62893081761
+2016-08-24 11:38:17,244 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:38:17,344 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:38:17,354 DEBUG: View 3 : 0.540880503145
+2016-08-24 11:38:17,573 DEBUG: Best view : RANSeq_
+2016-08-24 11:38:22,546 DEBUG: Start: Iteration 80
+2016-08-24 11:38:22,564 DEBUG: View 0 : 0.446540880503
+2016-08-24 11:38:22,573 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:38:22,677 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:38:22,686 DEBUG: View 3 : 0.496855345912
+2016-08-24 11:38:22,924 DEBUG: Best view : RANSeq_
+2016-08-24 11:38:28,195 DEBUG: Start: Iteration 81
+2016-08-24 11:38:28,212 DEBUG: View 0 : 0.578616352201
+2016-08-24 11:38:28,220 DEBUG: View 1 : 0.641509433962
+2016-08-24 11:38:28,320 DEBUG: View 2 : 0.610062893082
+2016-08-24 11:38:28,329 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:38:28,557 DEBUG: Best view : MiRNA__
+2016-08-24 11:38:33,641 DEBUG: Start: Iteration 82
+2016-08-24 11:38:33,657 DEBUG: View 0 : 0.572327044025
+2016-08-24 11:38:33,665 DEBUG: View 1 : 0.477987421384
+2016-08-24 11:38:33,762 DEBUG: View 2 : 0.635220125786
+2016-08-24 11:38:33,771 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:38:33,993 DEBUG: Best view : RANSeq_
+2016-08-24 11:38:39,134 DEBUG: Start: Iteration 83
+2016-08-24 11:38:39,151 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:38:39,159 DEBUG: View 1 : 0.62893081761
+2016-08-24 11:38:39,253 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:38:39,263 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:38:39,500 DEBUG: Best view : MiRNA__
+2016-08-24 11:38:44,911 DEBUG: Start: Iteration 84
+2016-08-24 11:38:44,928 DEBUG: View 0 : 0.641509433962
+2016-08-24 11:38:44,936 DEBUG: View 1 : 0.540880503145
+2016-08-24 11:38:45,031 DEBUG: View 2 : 0.459119496855
+2016-08-24 11:38:45,040 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:38:45,267 DEBUG: Best view : Clinic_
+2016-08-24 11:38:50,470 DEBUG: Start: Iteration 85
+2016-08-24 11:38:50,486 DEBUG: View 0 : 0.534591194969
+2016-08-24 11:38:50,494 DEBUG: View 1 : 0.566037735849
+2016-08-24 11:38:50,590 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:38:50,599 DEBUG: View 3 : 0.522012578616
+2016-08-24 11:38:50,827 DEBUG: Best view : RANSeq_
+2016-08-24 11:38:56,099 DEBUG: Start: Iteration 86
+2016-08-24 11:38:56,116 DEBUG: View 0 : 0.51572327044
+2016-08-24 11:38:56,123 DEBUG: View 1 : 0.767295597484
+2016-08-24 11:38:56,220 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:38:56,229 DEBUG: View 3 : 0.679245283019
+2016-08-24 11:38:56,464 DEBUG: Best view : MiRNA__
+2016-08-24 11:39:01,924 DEBUG: Start: Iteration 87
+2016-08-24 11:39:01,940 DEBUG: View 0 : 0.433962264151
+2016-08-24 11:39:01,948 DEBUG: View 1 : 0.389937106918
+2016-08-24 11:39:02,048 DEBUG: View 2 : 0.509433962264
+2016-08-24 11:39:02,057 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:39:02,293 DEBUG: Best view : Clinic_
+2016-08-24 11:39:07,876 DEBUG: Start: Iteration 88
+2016-08-24 11:39:07,892 DEBUG: View 0 : 0.59748427673
+2016-08-24 11:39:07,900 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:39:07,997 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:39:08,006 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:39:08,247 DEBUG: Best view : RANSeq_
+2016-08-24 11:39:13,795 DEBUG: Start: Iteration 89
+2016-08-24 11:39:13,812 DEBUG: View 0 : 0.389937106918
+2016-08-24 11:39:13,820 DEBUG: View 1 : 0.433962264151
+2016-08-24 11:39:13,916 DEBUG: View 2 : 0.477987421384
+2016-08-24 11:39:13,925 DEBUG: View 3 : 0.509433962264
+2016-08-24 11:39:14,169 DEBUG: Best view : Clinic_
+2016-08-24 11:39:19,785 DEBUG: Start: Iteration 90
+2016-08-24 11:39:19,801 DEBUG: View 0 : 0.654088050314
+2016-08-24 11:39:19,809 DEBUG: View 1 : 0.654088050314
+2016-08-24 11:39:19,908 DEBUG: View 2 : 0.540880503145
+2016-08-24 11:39:19,918 DEBUG: View 3 : 0.654088050314
+2016-08-24 11:39:20,158 DEBUG: Best view : Clinic_
+2016-08-24 11:39:25,716 DEBUG: Start: Iteration 91
+2016-08-24 11:39:25,732 DEBUG: View 0 : 0.635220125786
+2016-08-24 11:39:25,740 DEBUG: View 1 : 0.547169811321
+2016-08-24 11:39:25,840 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:39:25,849 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:39:26,091 DEBUG: Best view : Clinic_
+2016-08-24 11:39:31,685 DEBUG: Start: Iteration 92
+2016-08-24 11:39:31,702 DEBUG: View 0 : 0.654088050314
+2016-08-24 11:39:31,709 DEBUG: View 1 : 0.685534591195
+2016-08-24 11:39:31,807 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:39:31,816 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:39:32,060 DEBUG: Best view : MiRNA__
+2016-08-24 11:39:37,729 DEBUG: Start: Iteration 93
+2016-08-24 11:39:37,745 DEBUG: View 0 : 0.396226415094
+2016-08-24 11:39:37,753 DEBUG: View 1 : 0.62893081761
+2016-08-24 11:39:37,851 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:39:37,861 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:39:38,110 DEBUG: Best view : Clinic_
+2016-08-24 11:39:44,011 DEBUG: Start: Iteration 94
+2016-08-24 11:39:44,028 DEBUG: View 0 : 0.383647798742
+2016-08-24 11:39:44,036 DEBUG: View 1 : 0.591194968553
+2016-08-24 11:39:44,137 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:39:44,146 DEBUG: View 3 : 0.660377358491
+2016-08-24 11:39:44,399 DEBUG: Best view : Clinic_
+2016-08-24 11:39:50,390 DEBUG: Start: Iteration 95
+2016-08-24 11:39:50,407 DEBUG: View 0 : 0.679245283019
+2016-08-24 11:39:50,415 DEBUG: View 1 : 0.345911949686
+2016-08-24 11:39:50,516 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:39:50,525 DEBUG: View 3 : 0.660377358491
+2016-08-24 11:39:50,781 DEBUG: Best view : Clinic_
+2016-08-24 11:39:56,658 DEBUG: Start: Iteration 96
+2016-08-24 11:39:56,675 DEBUG: View 0 : 0.616352201258
+2016-08-24 11:39:56,682 DEBUG: View 1 : 0.660377358491
+2016-08-24 11:39:56,778 DEBUG: View 2 : 0.490566037736
+2016-08-24 11:39:56,787 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:39:57,047 DEBUG: Best view : MiRNA__
+2016-08-24 11:40:03,092 DEBUG: Start: Iteration 97
+2016-08-24 11:40:03,109 DEBUG: View 0 : 0.471698113208
+2016-08-24 11:40:03,117 DEBUG: View 1 : 0.433962264151
+2016-08-24 11:40:03,211 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:40:03,220 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:40:03,477 DEBUG: Best view : RANSeq_
+2016-08-24 11:40:09,639 DEBUG: Start: Iteration 98
+2016-08-24 11:40:09,655 DEBUG: View 0 : 0.352201257862
+2016-08-24 11:40:09,663 DEBUG: View 1 : 0.584905660377
+2016-08-24 11:40:09,757 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:40:09,766 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:40:10,022 DEBUG: Best view : Clinic_
+2016-08-24 11:40:16,036 DEBUG: Start: Iteration 99
+2016-08-24 11:40:16,052 DEBUG: View 0 : 0.553459119497
+2016-08-24 11:40:16,060 DEBUG: View 1 : 0.591194968553
+2016-08-24 11:40:16,156 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:40:16,165 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:40:16,423 DEBUG: Best view : MiRNA__
+2016-08-24 11:40:22,675 DEBUG: Start: Iteration 100
+2016-08-24 11:40:22,691 DEBUG: View 0 : 0.389937106918
+2016-08-24 11:40:22,698 DEBUG: View 1 : 0.433962264151
+2016-08-24 11:40:22,792 DEBUG: View 2 : 0.540880503145
+2016-08-24 11:40:22,801 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:40:23,061 DEBUG: Best view : Clinic_
+2016-08-24 11:40:29,412 DEBUG: Start: Iteration 101
+2016-08-24 11:40:29,429 DEBUG: View 0 : 0.572327044025
+2016-08-24 11:40:29,437 DEBUG: View 1 : 0.578616352201
+2016-08-24 11:40:29,545 DEBUG: View 2 : 0.584905660377
+2016-08-24 11:40:29,554 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:40:29,834 DEBUG: Best view : Clinic_
+2016-08-24 11:40:36,757 DEBUG: Start: Iteration 102
+2016-08-24 11:40:36,777 DEBUG: View 0 : 0.452830188679
+2016-08-24 11:40:36,787 DEBUG: View 1 : 0.345911949686
+2016-08-24 11:40:36,892 DEBUG: View 2 : 0.547169811321
+2016-08-24 11:40:36,903 DEBUG: View 3 : 0.553459119497
+2016-08-24 11:40:37,339 DEBUG: Best view : Clinic_
+2016-08-24 11:40:43,690 INFO: Start: Classification
+2016-08-24 11:40:58,693 INFO: Done: Fold number 2
+2016-08-24 11:40:58,693 INFO: Done: Classification
+2016-08-24 11:40:58,693 INFO: Info: Time for Classification: 756[s]
+2016-08-24 11:40:58,694 INFO: Start: Result Analysis for Mumbo
+2016-08-24 11:41:33,358 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 78.9774802191
+ -On Test : 77.868852459
+ -On Validation : 85.9223300971
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1, sub-sampled at 0.02 on Methyl
+ -DecisionTree with depth 1, sub-sampled at 0.02 on MiRNA
+ -DecisionTree with depth 1, sub-sampled at 0.1 on RNASEQ
+ -DecisionTree with depth 2, sub-sampled at 0.1 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0527741935484
+ - Percentage of time chosen : 0.906
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0553741935484
+ - Percentage of time chosen : 0.032
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0591741935484
+ - Percentage of time chosen : 0.03
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0589870967742
+ - Percentage of time chosen : 0.032
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0536855345912
+ - Percentage of time chosen : 0.904
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0556855345912
+ - Percentage of time chosen : 0.033
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0580943396226
+ - Percentage of time chosen : 0.022
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0596918238994
+ - Percentage of time chosen : 0.041
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 64.7798742138
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 75.7281553398
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 63.0350983972
+ Accuracy on test : 69.262295082
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 63.2258064516
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 64.7798742138
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 64.0028403327
+ Accuracy on test : 68.4426229508
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 63.2258064516
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 74.7572815534
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 71.6981132075
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 75.7281553398
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.4619598296
+ Accuracy on test : 72.131147541
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 63.2258064516
+ Accuracy on test : 70.4918032787
+ Accuracy on validation : 72.8155339806
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 72.3270440252
+ Accuracy on test : 66.393442623
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.7764252384
+ Accuracy on test : 68.4426229508
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 62.5806451613
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 78.6163522013
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.5984986813
+ Accuracy on test : 72.9508196721
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 64.5161290323
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 75.7281553398
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 75.4716981132
+ Accuracy on test : 68.8524590164
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 69.9939135727
+ Accuracy on test : 70.4918032787
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 66.4516129032
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 77.6699029126
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 80.5031446541
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 81.5533980583
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 73.4773787787
+ Accuracy on test : 74.5901639344
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 70.3225806452
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 82.5242718447
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 81.5533980583
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 73.8405356056
+ Accuracy on test : 73.3606557377
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 70.9677419355
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 81.5533980583
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 70.4918032787
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 75.1065124772
+ Accuracy on test : 73.3606557377
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 76.1290322581
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 78.6163522013
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.3726922297
+ Accuracy on test : 71.7213114754
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 74.1935483871
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 75.7760194766
+ Accuracy on test : 73.7704918033
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 74.8387096774
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 75.4716981132
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 75.1552038953
+ Accuracy on test : 77.868852459
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.2678027998
+ Accuracy on test : 77.0491803279
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 82.5242718447
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 82.3899371069
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.8723879083
+ Accuracy on test : 79.0983606557
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 85.534591195
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 82.4447149523
+ Accuracy on test : 77.4590163934
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.8742138365
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 80.9048488537
+ Accuracy on test : 79.0983606557
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 81.1320754717
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 81.8563603165
+ Accuracy on test : 80.3278688525
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 81.5533980583
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.6469872185
+ Accuracy on test : 78.6885245902
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.0099411645
+ Accuracy on test : 79.0983606557
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 80.0
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 78.6163522013
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.3081761006
+ Accuracy on test : 79.0983606557
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.6388719821
+ Accuracy on test : 78.2786885246
+ - Iteration 23
+ Fold 1
+ Accuracy on train : 80.0
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.9937106918
+ Accuracy on test : 79.0983606557
+ - Iteration 24
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 74.8427672956
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.0988030026
+ Accuracy on test : 79.5081967213
+ - Iteration 25
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 82.5242718447
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.9857983364
+ Accuracy on test : 81.5573770492
+ - Iteration 26
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 84.4660194175
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.6551024549
+ Accuracy on test : 80.3278688525
+ - Iteration 27
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.9695678637
+ Accuracy on test : 80.737704918
+ - Iteration 28
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.6551024549
+ Accuracy on test : 79.9180327869
+ - Iteration 29
+ Fold 1
+ Accuracy on train : 83.2258064516
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.6632176912
+ Accuracy on test : 80.737704918
+ - Iteration 30
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 74.213836478
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 82.5242718447
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.04240211
+ Accuracy on test : 80.3278688525
+ - Iteration 31
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 83.4951456311
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 80.3002637452
+ Accuracy on test : 80.737704918
+ - Iteration 32
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 83.4951456311
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 79.9857983364
+ Accuracy on test : 80.737704918
+ - Iteration 33
+ Fold 1
+ Accuracy on train : 84.5161290323
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 87.3786407767
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 75.4716981132
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 81.5533980583
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 79.9939135727
+ Accuracy on test : 81.9672131148
+ - Iteration 34
+ Fold 1
+ Accuracy on train : 84.5161290323
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.3083789815
+ Accuracy on test : 80.737704918
+ - Iteration 35
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 82.5242718447
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.614729154
+ Accuracy on test : 82.3770491803
+ - Iteration 36
+ Fold 1
+ Accuracy on train : 84.5161290323
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 81.251775208
+ Accuracy on test : 81.9672131148
+ - Iteration 37
+ Fold 1
+ Accuracy on train : 83.2258064516
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.6066139176
+ Accuracy on test : 81.9672131148
+ - Iteration 38
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.9291945628
+ Accuracy on test : 83.1967213115
+ - Iteration 39
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 85.4368932039
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.2840332725
+ Accuracy on test : 81.5573770492
+ - Iteration 40
+ Fold 1
+ Accuracy on train : 83.2258064516
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.6066139176
+ Accuracy on test : 81.5573770492
+ - Iteration 41
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.9614526273
+ Accuracy on test : 80.737704918
+ - Iteration 42
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 83.4951456311
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.3000608643
+ Accuracy on test : 80.3278688525
+ - Iteration 43
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 78.6163522013
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 85.4368932039
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.2759180361
+ Accuracy on test : 79.9180327869
+ - Iteration 44
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 83.4951456311
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 79.8742138365
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 79.6145262731
+ Accuracy on test : 79.5081967213
+ - Iteration 45
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.8742138365
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.9048488537
+ Accuracy on test : 79.5081967213
+ - Iteration 46
+ Fold 1
+ Accuracy on train : 80.6451612903
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 81.7610062893
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 87.3786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 81.2030837898
+ Accuracy on test : 80.737704918
+ - Iteration 47
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 84.4660194175
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 81.7610062893
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 87.3786407767
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 81.8482450801
+ Accuracy on test : 79.9180327869
+ - Iteration 48
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 80.5031446541
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 81.2193142625
+ Accuracy on test : 80.737704918
+ - Iteration 49
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 85.4368932039
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 80.2678027998
+ Accuracy on test : 78.6885245902
+ - Iteration 50
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 84.4660194175
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.5903834449
+ Accuracy on test : 79.5081967213
+ - Iteration 51
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.8742138365
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.5822682086
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+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:06:03 0:00:15
+ Fold 2 0:12:21 0:00:15
+ Total 0:18:25 0:00:30
+ So a total classification time of 0:12:36.
+
+
+2016-08-24 11:41:34,356 INFO: Done: Result Analysis
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-114134Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-114134Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..47196e88b46142dd89b1928f2b2d070ab765ff92
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-114134Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-114134Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-114134Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b8110dc4999a8522bda073b1c481fbc3a65c7b6f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-114134Results-Mumbo-Methyl-MiRNA-RNASEQ-Clinical-Yes-No-learnRate0.7-ModifiedMultiOmic.txt
@@ -0,0 +1,14060 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 78.9774802191
+ -On Test : 77.868852459
+ -On Validation : 85.9223300971
+
+Dataset info :
+ -Database name : ModifiedMultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA, RNASEQ, Clinical
+ -2 folds
+ - Validation set length : 103 for learning rate : 0.7
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 1000
+ -Weak Classifiers : DecisionTree with depth 1, sub-sampled at 0.02 on Methyl
+ -DecisionTree with depth 1, sub-sampled at 0.02 on MiRNA
+ -DecisionTree with depth 1, sub-sampled at 0.1 on RNASEQ
+ -DecisionTree with depth 2, sub-sampled at 0.1 on Clinical
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0527741935484
+ - Percentage of time chosen : 0.906
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0553741935484
+ - Percentage of time chosen : 0.032
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0591741935484
+ - Percentage of time chosen : 0.03
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0589870967742
+ - Percentage of time chosen : 0.032
+ - Fold 1
+ - On Methyl_ :
+ - Mean average Accuracy : 0.0536855345912
+ - Percentage of time chosen : 0.904
+ - On MiRNA__ :
+ - Mean average Accuracy : 0.0556855345912
+ - Percentage of time chosen : 0.033
+ - On RANSeq_ :
+ - Mean average Accuracy : 0.0580943396226
+ - Percentage of time chosen : 0.022
+ - On Clinic_ :
+ - Mean average Accuracy : 0.0596918238994
+ - Percentage of time chosen : 0.041
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 64.7798742138
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 75.7281553398
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 63.0350983972
+ Accuracy on test : 69.262295082
+ - Iteration 3
+ Fold 1
+ Accuracy on train : 63.2258064516
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 64.7798742138
+ Accuracy on test : 65.5737704918
+ Accuracy on validation : 75.7281553398
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 64.0028403327
+ Accuracy on test : 68.4426229508
+ - Iteration 4
+ Fold 1
+ Accuracy on train : 63.2258064516
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 74.7572815534
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 71.6981132075
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 75.7281553398
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.4619598296
+ Accuracy on test : 72.131147541
+ - Iteration 5
+ Fold 1
+ Accuracy on train : 63.2258064516
+ Accuracy on test : 70.4918032787
+ Accuracy on validation : 72.8155339806
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 72.3270440252
+ Accuracy on test : 66.393442623
+ Accuracy on validation : 79.6116504854
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 67.7764252384
+ Accuracy on test : 68.4426229508
+ - Iteration 6
+ Fold 1
+ Accuracy on train : 62.5806451613
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 74.7572815534
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 78.6163522013
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 70.5984986813
+ Accuracy on test : 72.9508196721
+ - Iteration 7
+ Fold 1
+ Accuracy on train : 64.5161290323
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 75.7281553398
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 75.4716981132
+ Accuracy on test : 68.8524590164
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 69.9939135727
+ Accuracy on test : 70.4918032787
+ - Iteration 8
+ Fold 1
+ Accuracy on train : 66.4516129032
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 77.6699029126
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 80.5031446541
+ Accuracy on test : 73.7704918033
+ Accuracy on validation : 81.5533980583
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 73.4773787787
+ Accuracy on test : 74.5901639344
+ - Iteration 9
+ Fold 1
+ Accuracy on train : 70.3225806452
+ Accuracy on test : 75.4098360656
+ Accuracy on validation : 82.5242718447
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 81.5533980583
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 73.8405356056
+ Accuracy on test : 73.3606557377
+ - Iteration 10
+ Fold 1
+ Accuracy on train : 70.9677419355
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 81.5533980583
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 70.4918032787
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 75.1065124772
+ Accuracy on test : 73.3606557377
+ - Iteration 11
+ Fold 1
+ Accuracy on train : 76.1290322581
+ Accuracy on test : 71.3114754098
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 78.6163522013
+ Accuracy on test : 72.131147541
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.3726922297
+ Accuracy on test : 71.7213114754
+ - Iteration 12
+ Fold 1
+ Accuracy on train : 74.1935483871
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 78.640776699
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 75.7760194766
+ Accuracy on test : 73.7704918033
+ - Iteration 13
+ Fold 1
+ Accuracy on train : 74.8387096774
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 80.5825242718
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 75.4716981132
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 75.1552038953
+ Accuracy on test : 77.868852459
+ - Iteration 14
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 74.5901639344
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.2678027998
+ Accuracy on test : 77.0491803279
+ - Iteration 15
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 82.5242718447
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 82.3899371069
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.8723879083
+ Accuracy on test : 79.0983606557
+ - Iteration 16
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 76.2295081967
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 85.534591195
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 82.4447149523
+ Accuracy on test : 77.4590163934
+ - Iteration 17
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 79.8742138365
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 80.9048488537
+ Accuracy on test : 79.0983606557
+ - Iteration 18
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 81.1320754717
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 81.8563603165
+ Accuracy on test : 80.3278688525
+ - Iteration 19
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 81.5533980583
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.6469872185
+ Accuracy on test : 78.6885245902
+ - Iteration 20
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.0099411645
+ Accuracy on test : 79.0983606557
+ - Iteration 21
+ Fold 1
+ Accuracy on train : 80.0
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 78.6163522013
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.3081761006
+ Accuracy on test : 79.0983606557
+ - Iteration 22
+ Fold 1
+ Accuracy on train : 81.2903225806
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.6388719821
+ Accuracy on test : 78.2786885246
+ - Iteration 23
+ Fold 1
+ Accuracy on train : 80.0
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 78.9937106918
+ Accuracy on test : 79.0983606557
+ - Iteration 24
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 74.8427672956
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 82.5242718447
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 77.0988030026
+ Accuracy on test : 79.5081967213
+ - Iteration 25
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 82.5242718447
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.9857983364
+ Accuracy on test : 81.5573770492
+ - Iteration 26
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 84.4660194175
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.6551024549
+ Accuracy on test : 80.3278688525
+ - Iteration 27
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 84.4660194175
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.9695678637
+ Accuracy on test : 80.737704918
+ - Iteration 28
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.6551024549
+ Accuracy on test : 79.9180327869
+ - Iteration 29
+ Fold 1
+ Accuracy on train : 83.2258064516
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 79.6632176912
+ Accuracy on test : 80.737704918
+ - Iteration 30
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 74.213836478
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 82.5242718447
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.04240211
+ Accuracy on test : 80.3278688525
+ - Iteration 31
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.7295597484
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 83.4951456311
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 80.3002637452
+ Accuracy on test : 80.737704918
+ - Iteration 32
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 81.9672131148
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 83.4951456311
+ Selected View : RANSeq_
+ - Mean :
+ Accuracy on train : 79.9857983364
+ Accuracy on test : 80.737704918
+ - Iteration 33
+ Fold 1
+ Accuracy on train : 84.5161290323
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 87.3786407767
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 75.4716981132
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 81.5533980583
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 79.9939135727
+ Accuracy on test : 81.9672131148
+ - Iteration 34
+ Fold 1
+ Accuracy on train : 84.5161290323
+ Accuracy on test : 82.7868852459
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 76.1006289308
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 80.5825242718
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.3083789815
+ Accuracy on test : 80.737704918
+ - Iteration 35
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 86.4077669903
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.358490566
+ Accuracy on test : 80.3278688525
+ Accuracy on validation : 82.5242718447
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.614729154
+ Accuracy on test : 82.3770491803
+ - Iteration 36
+ Fold 1
+ Accuracy on train : 84.5161290323
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 79.5081967213
+ Accuracy on validation : 83.4951456311
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 81.251775208
+ Accuracy on test : 81.9672131148
+ - Iteration 37
+ Fold 1
+ Accuracy on train : 83.2258064516
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 85.4368932039
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.6066139176
+ Accuracy on test : 81.9672131148
+ - Iteration 38
+ Fold 1
+ Accuracy on train : 83.8709677419
+ Accuracy on test : 85.2459016393
+ Accuracy on validation : 87.3786407767
+ Selected View : MiRNA__
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 81.1475409836
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.9291945628
+ Accuracy on test : 83.1967213115
+ - Iteration 39
+ Fold 1
+ Accuracy on train : 82.5806451613
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 86.4077669903
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 85.4368932039
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 80.2840332725
+ Accuracy on test : 81.5573770492
+ - Iteration 40
+ Fold 1
+ Accuracy on train : 83.2258064516
+ Accuracy on test : 84.4262295082
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 78.6885245902
+ Accuracy on validation : 83.4951456311
+ Selected View : MiRNA__
+ - Mean :
+ Accuracy on train : 80.6066139176
+ Accuracy on test : 81.5573770492
+ - Iteration 41
+ Fold 1
+ Accuracy on train : 81.935483871
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 85.4368932039
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 77.9874213836
+ Accuracy on test : 77.868852459
+ Accuracy on validation : 84.4660194175
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.9614526273
+ Accuracy on test : 80.737704918
+ - Iteration 42
+ Fold 1
+ Accuracy on train : 79.3548387097
+ Accuracy on test : 83.606557377
+ Accuracy on validation : 83.4951456311
+ Selected View : RANSeq_
+ Fold 2
+ Accuracy on train : 79.2452830189
+ Accuracy on test : 77.0491803279
+ Accuracy on validation : 86.4077669903
+ Selected View : Clinic_
+ - Mean :
+ Accuracy on train : 79.3000608643
+ Accuracy on test : 80.3278688525
+ - Iteration 43
+ Fold 1
+ Accuracy on train : 81.935483871
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+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 990
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 991
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 992
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 993
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 994
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 995
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 996
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 997
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 998
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 999
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+ - Iteration 1000
+ Fold 1
+ Accuracy on train : 61.2903225806
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ Fold 2
+ Accuracy on train : 62.2641509434
+ Accuracy on test : 72.9508196721
+ Accuracy on validation : 73.786407767
+ Selected View : Methyl_
+ - Mean :
+ Accuracy on train : 61.777236762
+ Accuracy on test : 72.9508196721
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:06:03 0:00:15
+ Fold 2 0:12:21 0:00:15
+ Total 0:18:25 0:00:30
+ So a total classification time of 0:12:36.
+
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-115022-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-115022-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..e8da32671bbba0aa021a3faeea30a177249702f9
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-115022-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,655 @@
+2016-08-24 11:50:22,490 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 11:50:22,491 INFO: Info: Labels used: No, Yes
+2016-08-24 11:50:22,491 INFO: Info: Length of dataset:347
+2016-08-24 11:50:22,493 INFO: ### Main Programm for Multiview Classification
+2016-08-24 11:50:22,493 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 11:50:22,493 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 11:50:22,494 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 11:50:22,494 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 11:50:22,494 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 11:50:22,495 INFO: Done: Read Database Files
+2016-08-24 11:50:22,495 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 11:50:22,498 INFO: Done: Determine validation split
+2016-08-24 11:50:22,498 INFO: Start: Determine 2 folds
+2016-08-24 11:50:22,508 INFO: Info: Length of Learning Sets: 122
+2016-08-24 11:50:22,508 INFO: Info: Length of Testing Sets: 122
+2016-08-24 11:50:22,508 INFO: Info: Length of Validation Set: 103
+2016-08-24 11:50:22,509 INFO: Done: Determine folds
+2016-08-24 11:50:22,509 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 11:50:22,509 INFO: Start: Fold number 1
+2016-08-24 11:50:24,147 DEBUG: Start: Iteration 1
+2016-08-24 11:50:24,169 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:50:24,180 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:50:24,222 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:50:24,230 DEBUG: View 3 : 0.471698113208
+2016-08-24 11:50:24,276 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:24,364 DEBUG: Start: Iteration 2
+2016-08-24 11:50:24,382 DEBUG: View 0 : 0.477987421384
+2016-08-24 11:50:24,390 DEBUG: View 1 : 0.591194968553
+2016-08-24 11:50:24,491 DEBUG: View 2 : 0.610062893082
+2016-08-24 11:50:24,499 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:50:24,557 DEBUG: Best view : RANSeq_
+2016-08-24 11:50:24,711 DEBUG: Start: Iteration 3
+2016-08-24 11:50:24,728 DEBUG: View 0 : 0.345911949686
+2016-08-24 11:50:24,737 DEBUG: View 1 : 0.48427672956
+2016-08-24 11:50:24,825 DEBUG: View 2 : 0.540880503145
+2016-08-24 11:50:24,833 DEBUG: View 3 : 0.660377358491
+2016-08-24 11:50:24,890 DEBUG: Best view : Clinic_
+2016-08-24 11:50:25,106 DEBUG: Start: Iteration 4
+2016-08-24 11:50:25,124 DEBUG: View 0 : 0.427672955975
+2016-08-24 11:50:25,132 DEBUG: View 1 : 0.496855345912
+2016-08-24 11:50:25,223 DEBUG: View 2 : 0.698113207547
+2016-08-24 11:50:25,231 DEBUG: View 3 : 0.566037735849
+2016-08-24 11:50:25,293 DEBUG: Best view : RANSeq_
+2016-08-24 11:50:25,589 DEBUG: Start: Iteration 5
+2016-08-24 11:50:25,610 DEBUG: View 0 : 0.503144654088
+2016-08-24 11:50:25,626 DEBUG: View 1 : 0.603773584906
+2016-08-24 11:50:25,714 DEBUG: View 2 : 0.522012578616
+2016-08-24 11:50:25,722 DEBUG: View 3 : 0.647798742138
+2016-08-24 11:50:25,785 DEBUG: Best view : Clinic_
+2016-08-24 11:50:26,134 DEBUG: Start: Iteration 6
+2016-08-24 11:50:26,151 DEBUG: View 0 : 0.40251572327
+2016-08-24 11:50:26,159 DEBUG: View 1 : 0.704402515723
+2016-08-24 11:50:26,249 DEBUG: View 2 : 0.547169811321
+2016-08-24 11:50:26,257 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:50:26,320 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:26,737 DEBUG: Start: Iteration 7
+2016-08-24 11:50:26,754 DEBUG: View 0 : 0.51572327044
+2016-08-24 11:50:26,762 DEBUG: View 1 : 0.48427672956
+2016-08-24 11:50:26,851 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:50:26,859 DEBUG: View 3 : 0.610062893082
+2016-08-24 11:50:26,925 DEBUG: Best view : Clinic_
+2016-08-24 11:50:27,480 DEBUG: Start: Iteration 8
+2016-08-24 11:50:27,500 DEBUG: View 0 : 0.635220125786
+2016-08-24 11:50:27,513 DEBUG: View 1 : 0.389937106918
+2016-08-24 11:50:27,646 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:50:27,661 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:50:27,774 DEBUG: Best view : Methyl_
+2016-08-24 11:50:28,343 DEBUG: Start: Iteration 9
+2016-08-24 11:50:28,360 DEBUG: View 0 : 0.440251572327
+2016-08-24 11:50:28,368 DEBUG: View 1 : 0.528301886792
+2016-08-24 11:50:28,458 DEBUG: View 2 : 0.641509433962
+2016-08-24 11:50:28,466 DEBUG: View 3 : 0.603773584906
+2016-08-24 11:50:28,538 DEBUG: Best view : RANSeq_
+2016-08-24 11:50:29,134 DEBUG: Start: Iteration 10
+2016-08-24 11:50:29,150 DEBUG: View 0 : 0.37106918239
+2016-08-24 11:50:29,158 DEBUG: View 1 : 0.660377358491
+2016-08-24 11:50:29,248 DEBUG: View 2 : 0.48427672956
+2016-08-24 11:50:29,256 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:50:29,328 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:29,975 DEBUG: Start: Iteration 11
+2016-08-24 11:50:29,992 DEBUG: View 0 : 0.446540880503
+2016-08-24 11:50:29,999 DEBUG: View 1 : 0.691823899371
+2016-08-24 11:50:30,091 DEBUG: View 2 : 0.48427672956
+2016-08-24 11:50:30,098 DEBUG: View 3 : 0.610062893082
+2016-08-24 11:50:30,172 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:30,885 DEBUG: Start: Iteration 12
+2016-08-24 11:50:30,902 DEBUG: View 0 : 0.408805031447
+2016-08-24 11:50:30,909 DEBUG: View 1 : 0.377358490566
+2016-08-24 11:50:30,995 DEBUG: View 2 : 0.616352201258
+2016-08-24 11:50:31,004 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:50:31,080 DEBUG: Best view : RANSeq_
+2016-08-24 11:50:31,869 DEBUG: Start: Iteration 13
+2016-08-24 11:50:31,885 DEBUG: View 0 : 0.415094339623
+2016-08-24 11:50:31,893 DEBUG: View 1 : 0.578616352201
+2016-08-24 11:50:31,978 DEBUG: View 2 : 0.603773584906
+2016-08-24 11:50:31,986 DEBUG: View 3 : 0.641509433962
+2016-08-24 11:50:32,067 DEBUG: Best view : Clinic_
+2016-08-24 11:50:32,908 DEBUG: Start: Iteration 14
+2016-08-24 11:50:32,924 DEBUG: View 0 : 0.440251572327
+2016-08-24 11:50:32,932 DEBUG: View 1 : 0.654088050314
+2016-08-24 11:50:33,013 DEBUG: View 2 : 0.603773584906
+2016-08-24 11:50:33,020 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:50:33,100 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:33,998 DEBUG: Start: Iteration 15
+2016-08-24 11:50:34,015 DEBUG: View 0 : 0.616352201258
+2016-08-24 11:50:34,022 DEBUG: View 1 : 0.584905660377
+2016-08-24 11:50:34,108 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:50:34,116 DEBUG: View 3 : 0.660377358491
+2016-08-24 11:50:34,198 DEBUG: Best view : Clinic_
+2016-08-24 11:50:35,164 DEBUG: Start: Iteration 16
+2016-08-24 11:50:35,181 DEBUG: View 0 : 0.358490566038
+2016-08-24 11:50:35,189 DEBUG: View 1 : 0.641509433962
+2016-08-24 11:50:35,278 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:50:35,286 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:50:35,370 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:36,375 DEBUG: Start: Iteration 17
+2016-08-24 11:50:36,391 DEBUG: View 0 : 0.477987421384
+2016-08-24 11:50:36,399 DEBUG: View 1 : 0.698113207547
+2016-08-24 11:50:36,489 DEBUG: View 2 : 0.660377358491
+2016-08-24 11:50:36,496 DEBUG: View 3 : 0.610062893082
+2016-08-24 11:50:36,583 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:37,656 DEBUG: Start: Iteration 18
+2016-08-24 11:50:37,672 DEBUG: View 0 : 0.389937106918
+2016-08-24 11:50:37,680 DEBUG: View 1 : 0.584905660377
+2016-08-24 11:50:37,770 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:50:37,778 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:50:37,866 DEBUG: Best view : Clinic_
+2016-08-24 11:50:38,996 DEBUG: Start: Iteration 19
+2016-08-24 11:50:39,013 DEBUG: View 0 : 0.591194968553
+2016-08-24 11:50:39,020 DEBUG: View 1 : 0.251572327044
+2016-08-24 11:50:39,101 DEBUG: View 2 : 0.547169811321
+2016-08-24 11:50:39,109 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:50:39,199 DEBUG: Best view : Clinic_
+2016-08-24 11:50:40,389 DEBUG: Start: Iteration 20
+2016-08-24 11:50:40,406 DEBUG: View 0 : 0.578616352201
+2016-08-24 11:50:40,414 DEBUG: View 1 : 0.691823899371
+2016-08-24 11:50:40,500 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:50:40,508 DEBUG: View 3 : 0.534591194969
+2016-08-24 11:50:40,600 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:41,849 DEBUG: Start: Iteration 21
+2016-08-24 11:50:41,866 DEBUG: View 0 : 0.553459119497
+2016-08-24 11:50:41,873 DEBUG: View 1 : 0.522012578616
+2016-08-24 11:50:41,960 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:50:41,968 DEBUG: View 3 : 0.509433962264
+2016-08-24 11:50:42,063 DEBUG: Best view : RANSeq_
+2016-08-24 11:50:43,380 DEBUG: Start: Iteration 22
+2016-08-24 11:50:43,397 DEBUG: View 0 : 0.48427672956
+2016-08-24 11:50:43,405 DEBUG: View 1 : 0.440251572327
+2016-08-24 11:50:43,494 DEBUG: View 2 : 0.509433962264
+2016-08-24 11:50:43,502 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:50:43,600 DEBUG: Best view : Clinic_
+2016-08-24 11:50:44,988 DEBUG: Start: Iteration 23
+2016-08-24 11:50:45,005 DEBUG: View 0 : 0.622641509434
+2016-08-24 11:50:45,013 DEBUG: View 1 : 0.559748427673
+2016-08-24 11:50:45,102 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:50:45,110 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:50:45,209 DEBUG: Best view : Methyl_
+2016-08-24 11:50:46,651 DEBUG: Start: Iteration 24
+2016-08-24 11:50:46,668 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:50:46,675 DEBUG: View 1 : 0.704402515723
+2016-08-24 11:50:46,758 DEBUG: View 2 : 0.547169811321
+2016-08-24 11:50:46,766 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:50:46,867 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:48,357 DEBUG: Start: Iteration 25
+2016-08-24 11:50:48,374 DEBUG: View 0 : 0.641509433962
+2016-08-24 11:50:48,381 DEBUG: View 1 : 0.534591194969
+2016-08-24 11:50:48,472 DEBUG: View 2 : 0.496855345912
+2016-08-24 11:50:48,480 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:50:48,583 DEBUG: Best view : Methyl_
+2016-08-24 11:50:50,137 DEBUG: Start: Iteration 26
+2016-08-24 11:50:50,153 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:50:50,161 DEBUG: View 1 : 0.672955974843
+2016-08-24 11:50:50,254 DEBUG: View 2 : 0.647798742138
+2016-08-24 11:50:50,262 DEBUG: View 3 : 0.490566037736
+2016-08-24 11:50:50,368 DEBUG: Best view : MiRNA__
+2016-08-24 11:50:51,980 DEBUG: Start: Iteration 27
+2016-08-24 11:50:51,997 DEBUG: View 0 : 0.710691823899
+2016-08-24 11:50:52,005 DEBUG: View 1 : 0.591194968553
+2016-08-24 11:50:52,092 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:50:52,100 DEBUG: View 3 : 0.654088050314
+2016-08-24 11:50:52,208 DEBUG: Best view : Methyl_
+2016-08-24 11:50:53,885 DEBUG: Start: Iteration 28
+2016-08-24 11:50:53,902 DEBUG: View 0 : 0.672955974843
+2016-08-24 11:50:53,909 DEBUG: View 1 : 0.408805031447
+2016-08-24 11:50:53,997 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:50:54,005 DEBUG: View 3 : 0.622641509434
+2016-08-24 11:50:54,115 DEBUG: Best view : Methyl_
+2016-08-24 11:50:55,861 DEBUG: Start: Iteration 29
+2016-08-24 11:50:55,878 DEBUG: View 0 : 0.408805031447
+2016-08-24 11:50:55,886 DEBUG: View 1 : 0.540880503145
+2016-08-24 11:50:55,971 DEBUG: View 2 : 0.528301886792
+2016-08-24 11:50:55,979 DEBUG: View 3 : 0.522012578616
+2016-08-24 11:50:56,093 DEBUG: Best view : RANSeq_
+2016-08-24 11:50:57,922 DEBUG: Start: Iteration 30
+2016-08-24 11:50:57,939 DEBUG: View 0 : 0.408805031447
+2016-08-24 11:50:57,946 DEBUG: View 1 : 0.383647798742
+2016-08-24 11:50:58,039 DEBUG: View 2 : 0.540880503145
+2016-08-24 11:50:58,047 DEBUG: View 3 : 0.534591194969
+2016-08-24 11:50:58,162 DEBUG: Best view : RANSeq_
+2016-08-24 11:51:00,061 DEBUG: Start: Iteration 31
+2016-08-24 11:51:00,078 DEBUG: View 0 : 0.358490566038
+2016-08-24 11:51:00,086 DEBUG: View 1 : 0.528301886792
+2016-08-24 11:51:00,176 DEBUG: View 2 : 0.528301886792
+2016-08-24 11:51:00,184 DEBUG: View 3 : 0.622641509434
+2016-08-24 11:51:00,301 DEBUG: Best view : Clinic_
+2016-08-24 11:51:02,266 DEBUG: Start: Iteration 32
+2016-08-24 11:51:02,284 DEBUG: View 0 : 0.377358490566
+2016-08-24 11:51:02,292 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:51:02,388 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:51:02,396 DEBUG: View 3 : 0.522012578616
+2016-08-24 11:51:02,517 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:04,541 DEBUG: Start: Iteration 33
+2016-08-24 11:51:04,557 DEBUG: View 0 : 0.345911949686
+2016-08-24 11:51:04,566 DEBUG: View 1 : 0.654088050314
+2016-08-24 11:51:04,663 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:51:04,671 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:51:04,794 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:06,888 DEBUG: Start: Iteration 34
+2016-08-24 11:51:06,904 DEBUG: View 0 : 0.622641509434
+2016-08-24 11:51:06,912 DEBUG: View 1 : 0.566037735849
+2016-08-24 11:51:06,992 DEBUG: View 2 : 0.522012578616
+2016-08-24 11:51:07,001 DEBUG: View 3 : 0.647798742138
+2016-08-24 11:51:07,125 DEBUG: Best view : Clinic_
+2016-08-24 11:51:09,330 DEBUG: Start: Iteration 35
+2016-08-24 11:51:09,347 DEBUG: View 0 : 0.452830188679
+2016-08-24 11:51:09,355 DEBUG: View 1 : 0.635220125786
+2016-08-24 11:51:09,453 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:51:09,462 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:51:09,592 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:11,779 DEBUG: Start: Iteration 36
+2016-08-24 11:51:11,796 DEBUG: View 0 : 0.572327044025
+2016-08-24 11:51:11,804 DEBUG: View 1 : 0.540880503145
+2016-08-24 11:51:11,891 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:51:11,899 DEBUG: View 3 : 0.603773584906
+2016-08-24 11:51:12,026 DEBUG: Best view : Clinic_
+2016-08-24 11:51:14,260 DEBUG: Start: Iteration 37
+2016-08-24 11:51:14,277 DEBUG: View 0 : 0.490566037736
+2016-08-24 11:51:14,285 DEBUG: View 1 : 0.433962264151
+2016-08-24 11:51:14,380 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:51:14,389 DEBUG: View 3 : 0.679245283019
+2016-08-24 11:51:14,518 DEBUG: Best view : Clinic_
+2016-08-24 11:51:16,845 DEBUG: Start: Iteration 38
+2016-08-24 11:51:16,862 DEBUG: View 0 : 0.452830188679
+2016-08-24 11:51:16,870 DEBUG: View 1 : 0.496855345912
+2016-08-24 11:51:16,959 DEBUG: View 2 : 0.503144654088
+2016-08-24 11:51:16,967 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:51:17,099 DEBUG: Best view : Clinic_
+2016-08-24 11:51:19,449 DEBUG: Start: Iteration 39
+2016-08-24 11:51:19,466 DEBUG: View 0 : 0.603773584906
+2016-08-24 11:51:19,473 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:51:19,563 DEBUG: View 2 : 0.540880503145
+2016-08-24 11:51:19,571 DEBUG: View 3 : 0.477987421384
+2016-08-24 11:51:19,705 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:22,122 DEBUG: Start: Iteration 40
+2016-08-24 11:51:22,139 DEBUG: View 0 : 0.559748427673
+2016-08-24 11:51:22,147 DEBUG: View 1 : 0.672955974843
+2016-08-24 11:51:22,236 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:51:22,245 DEBUG: View 3 : 0.666666666667
+2016-08-24 11:51:22,381 DEBUG: Best view : Clinic_
+2016-08-24 11:51:24,842 DEBUG: Start: Iteration 41
+2016-08-24 11:51:24,859 DEBUG: View 0 : 0.421383647799
+2016-08-24 11:51:24,867 DEBUG: View 1 : 0.660377358491
+2016-08-24 11:51:24,950 DEBUG: View 2 : 0.616352201258
+2016-08-24 11:51:24,959 DEBUG: View 3 : 0.553459119497
+2016-08-24 11:51:25,097 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:27,616 DEBUG: Start: Iteration 42
+2016-08-24 11:51:27,633 DEBUG: View 0 : 0.509433962264
+2016-08-24 11:51:27,641 DEBUG: View 1 : 0.660377358491
+2016-08-24 11:51:27,734 DEBUG: View 2 : 0.522012578616
+2016-08-24 11:51:27,742 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:51:27,882 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:30,452 DEBUG: Start: Iteration 43
+2016-08-24 11:51:30,469 DEBUG: View 0 : 0.616352201258
+2016-08-24 11:51:30,477 DEBUG: View 1 : 0.534591194969
+2016-08-24 11:51:30,572 DEBUG: View 2 : 0.509433962264
+2016-08-24 11:51:30,581 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:51:30,723 DEBUG: Best view : Methyl_
+2016-08-24 11:51:33,333 DEBUG: Start: Iteration 44
+2016-08-24 11:51:33,349 DEBUG: View 0 : 0.660377358491
+2016-08-24 11:51:33,357 DEBUG: View 1 : 0.440251572327
+2016-08-24 11:51:33,455 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:51:33,464 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:51:33,607 DEBUG: Best view : Methyl_
+2016-08-24 11:51:36,279 DEBUG: Start: Iteration 45
+2016-08-24 11:51:36,296 DEBUG: View 0 : 0.51572327044
+2016-08-24 11:51:36,304 DEBUG: View 1 : 0.59748427673
+2016-08-24 11:51:36,400 DEBUG: View 2 : 0.660377358491
+2016-08-24 11:51:36,409 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:51:36,556 DEBUG: Best view : RANSeq_
+2016-08-24 11:51:39,318 DEBUG: Start: Iteration 46
+2016-08-24 11:51:39,334 DEBUG: View 0 : 0.490566037736
+2016-08-24 11:51:39,342 DEBUG: View 1 : 0.647798742138
+2016-08-24 11:51:39,437 DEBUG: View 2 : 0.534591194969
+2016-08-24 11:51:39,447 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:51:39,596 DEBUG: Best view : Clinic_
+2016-08-24 11:51:42,394 DEBUG: Start: Iteration 47
+2016-08-24 11:51:42,410 DEBUG: View 0 : 0.578616352201
+2016-08-24 11:51:42,418 DEBUG: View 1 : 0.647798742138
+2016-08-24 11:51:42,514 DEBUG: View 2 : 0.547169811321
+2016-08-24 11:51:42,522 DEBUG: View 3 : 0.503144654088
+2016-08-24 11:51:42,673 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:45,517 DEBUG: Start: Iteration 48
+2016-08-24 11:51:45,533 DEBUG: View 0 : 0.433962264151
+2016-08-24 11:51:45,541 DEBUG: View 1 : 0.522012578616
+2016-08-24 11:51:45,630 DEBUG: View 2 : 0.616352201258
+2016-08-24 11:51:45,637 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:51:45,789 DEBUG: Best view : RANSeq_
+2016-08-24 11:51:48,860 DEBUG: Start: Iteration 49
+2016-08-24 11:51:48,876 DEBUG: View 0 : 0.616352201258
+2016-08-24 11:51:48,884 DEBUG: View 1 : 0.635220125786
+2016-08-24 11:51:48,972 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:51:48,980 DEBUG: View 3 : 0.603773584906
+2016-08-24 11:51:49,140 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:52,141 DEBUG: Start: Iteration 50
+2016-08-24 11:51:52,158 DEBUG: View 0 : 0.503144654088
+2016-08-24 11:51:52,166 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:51:52,255 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:51:52,263 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:51:52,421 DEBUG: Best view : MiRNA__
+2016-08-24 11:51:55,452 DEBUG: Start: Iteration 51
+2016-08-24 11:51:55,469 DEBUG: View 0 : 0.528301886792
+2016-08-24 11:51:55,477 DEBUG: View 1 : 0.62893081761
+2016-08-24 11:51:55,564 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:51:55,572 DEBUG: View 3 : 0.679245283019
+2016-08-24 11:51:55,731 DEBUG: Best view : Clinic_
+2016-08-24 11:51:58,822 DEBUG: Start: Iteration 52
+2016-08-24 11:51:58,839 DEBUG: View 0 : 0.40251572327
+2016-08-24 11:51:58,847 DEBUG: View 1 : 0.358490566038
+2016-08-24 11:51:58,937 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:51:58,944 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:51:59,110 DEBUG: Best view : RANSeq_
+2016-08-24 11:52:02,297 DEBUG: Start: Iteration 53
+2016-08-24 11:52:02,314 DEBUG: View 0 : 0.377358490566
+2016-08-24 11:52:02,321 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:52:02,411 DEBUG: View 2 : 0.509433962264
+2016-08-24 11:52:02,419 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:52:02,583 DEBUG: Best view : MiRNA__
+2016-08-24 11:52:05,819 DEBUG: Start: Iteration 54
+2016-08-24 11:52:05,836 DEBUG: View 0 : 0.572327044025
+2016-08-24 11:52:05,844 DEBUG: View 1 : 0.647798742138
+2016-08-24 11:52:05,941 DEBUG: View 2 : 0.603773584906
+2016-08-24 11:52:05,949 DEBUG: View 3 : 0.641509433962
+2016-08-24 11:52:06,118 DEBUG: Best view : Clinic_
+2016-08-24 11:52:09,420 DEBUG: Start: Iteration 55
+2016-08-24 11:52:09,437 DEBUG: View 0 : 0.654088050314
+2016-08-24 11:52:09,445 DEBUG: View 1 : 0.427672955975
+2016-08-24 11:52:09,525 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:52:09,533 DEBUG: View 3 : 0.528301886792
+2016-08-24 11:52:09,700 DEBUG: Best view : Methyl_
+2016-08-24 11:52:13,042 DEBUG: Start: Iteration 56
+2016-08-24 11:52:13,058 DEBUG: View 0 : 0.37106918239
+2016-08-24 11:52:13,066 DEBUG: View 1 : 0.748427672956
+2016-08-24 11:52:13,150 DEBUG: View 2 : 0.584905660377
+2016-08-24 11:52:13,157 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:52:13,330 DEBUG: Best view : MiRNA__
+2016-08-24 11:52:16,739 DEBUG: Start: Iteration 57
+2016-08-24 11:52:16,756 DEBUG: View 0 : 0.805031446541
+2016-08-24 11:52:16,764 DEBUG: View 1 : 0.471698113208
+2016-08-24 11:52:16,851 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:52:16,858 DEBUG: View 3 : 0.616352201258
+2016-08-24 11:52:17,034 DEBUG: Best view : Methyl_
+2016-08-24 11:52:20,629 DEBUG: Start: Iteration 58
+2016-08-24 11:52:20,646 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:52:20,653 DEBUG: View 1 : 0.352201257862
+2016-08-24 11:52:20,738 DEBUG: View 2 : 0.647798742138
+2016-08-24 11:52:20,745 DEBUG: View 3 : 0.490566037736
+2016-08-24 11:52:20,924 DEBUG: Best view : RANSeq_
+2016-08-24 11:52:24,455 DEBUG: Start: Iteration 59
+2016-08-24 11:52:24,471 DEBUG: View 0 : 0.301886792453
+2016-08-24 11:52:24,479 DEBUG: View 1 : 0.333333333333
+2016-08-24 11:52:24,562 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:52:24,570 DEBUG: View 3 : 0.616352201258
+2016-08-24 11:52:24,747 DEBUG: Best view : Clinic_
+2016-08-24 11:52:28,327 DEBUG: Start: Iteration 60
+2016-08-24 11:52:28,344 DEBUG: View 0 : 0.559748427673
+2016-08-24 11:52:28,352 DEBUG: View 1 : 0.591194968553
+2016-08-24 11:52:28,439 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:52:28,447 DEBUG: View 3 : 0.446540880503
+2016-08-24 11:52:28,627 DEBUG: Best view : MiRNA__
+2016-08-24 11:52:32,268 DEBUG: Start: Iteration 61
+2016-08-24 11:52:32,284 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:52:32,292 DEBUG: View 1 : 0.691823899371
+2016-08-24 11:52:32,379 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:52:32,387 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:52:32,568 DEBUG: Best view : MiRNA__
+2016-08-24 11:52:36,264 DEBUG: Start: Iteration 62
+2016-08-24 11:52:36,281 DEBUG: View 0 : 0.748427672956
+2016-08-24 11:52:36,288 DEBUG: View 1 : 0.528301886792
+2016-08-24 11:52:36,377 DEBUG: View 2 : 0.672955974843
+2016-08-24 11:52:36,384 DEBUG: View 3 : 0.691823899371
+2016-08-24 11:52:36,569 DEBUG: Best view : Methyl_
+2016-08-24 11:52:40,347 DEBUG: Start: Iteration 63
+2016-08-24 11:52:40,363 DEBUG: View 0 : 0.465408805031
+2016-08-24 11:52:40,371 DEBUG: View 1 : 0.622641509434
+2016-08-24 11:52:40,459 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:52:40,467 DEBUG: View 3 : 0.553459119497
+2016-08-24 11:52:40,655 DEBUG: Best view : MiRNA__
+2016-08-24 11:52:44,468 DEBUG: Start: Iteration 64
+2016-08-24 11:52:44,484 DEBUG: View 0 : 0.610062893082
+2016-08-24 11:52:44,492 DEBUG: View 1 : 0.566037735849
+2016-08-24 11:52:44,580 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:52:44,588 DEBUG: View 3 : 0.622641509434
+2016-08-24 11:52:44,777 DEBUG: Best view : RANSeq_
+2016-08-24 11:52:48,671 DEBUG: Start: Iteration 65
+2016-08-24 11:52:48,688 DEBUG: View 0 : 0.427672955975
+2016-08-24 11:52:48,696 DEBUG: View 1 : 0.383647798742
+2016-08-24 11:52:48,780 DEBUG: View 2 : 0.584905660377
+2016-08-24 11:52:48,788 DEBUG: View 3 : 0.566037735849
+2016-08-24 11:52:48,978 DEBUG: Best view : RANSeq_
+2016-08-24 11:52:52,930 DEBUG: Start: Iteration 66
+2016-08-24 11:52:52,947 DEBUG: View 0 : 0.383647798742
+2016-08-24 11:52:52,955 DEBUG: View 1 : 0.616352201258
+2016-08-24 11:52:53,044 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:52:53,052 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:52:53,245 DEBUG: Best view : Clinic_
+2016-08-24 11:52:57,247 DEBUG: Start: Iteration 67
+2016-08-24 11:52:57,264 DEBUG: View 0 : 0.459119496855
+2016-08-24 11:52:57,271 DEBUG: View 1 : 0.421383647799
+2016-08-24 11:52:57,359 DEBUG: View 2 : 0.522012578616
+2016-08-24 11:52:57,367 DEBUG: View 3 : 0.603773584906
+2016-08-24 11:52:57,561 DEBUG: Best view : Clinic_
+2016-08-24 11:53:01,624 DEBUG: Start: Iteration 68
+2016-08-24 11:53:01,640 DEBUG: View 0 : 0.62893081761
+2016-08-24 11:53:01,648 DEBUG: View 1 : 0.503144654088
+2016-08-24 11:53:01,739 DEBUG: View 2 : 0.534591194969
+2016-08-24 11:53:01,747 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:53:01,944 DEBUG: Best view : Methyl_
+2016-08-24 11:53:06,061 DEBUG: Start: Iteration 69
+2016-08-24 11:53:06,078 DEBUG: View 0 : 0.578616352201
+2016-08-24 11:53:06,085 DEBUG: View 1 : 0.389937106918
+2016-08-24 11:53:06,174 DEBUG: View 2 : 0.572327044025
+2016-08-24 11:53:06,182 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:53:06,383 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:10,572 DEBUG: Start: Iteration 70
+2016-08-24 11:53:10,588 DEBUG: View 0 : 0.48427672956
+2016-08-24 11:53:10,596 DEBUG: View 1 : 0.635220125786
+2016-08-24 11:53:10,680 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:53:10,687 DEBUG: View 3 : 0.59748427673
+2016-08-24 11:53:10,888 DEBUG: Best view : Clinic_
+2016-08-24 11:53:15,144 DEBUG: Start: Iteration 71
+2016-08-24 11:53:15,160 DEBUG: View 0 : 0.622641509434
+2016-08-24 11:53:15,168 DEBUG: View 1 : 0.509433962264
+2016-08-24 11:53:15,258 DEBUG: View 2 : 0.616352201258
+2016-08-24 11:53:15,266 DEBUG: View 3 : 0.528301886792
+2016-08-24 11:53:15,469 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:19,842 DEBUG: Start: Iteration 72
+2016-08-24 11:53:19,858 DEBUG: View 0 : 0.446540880503
+2016-08-24 11:53:19,866 DEBUG: View 1 : 0.610062893082
+2016-08-24 11:53:19,954 DEBUG: View 2 : 0.635220125786
+2016-08-24 11:53:19,962 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:53:20,164 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:24,556 DEBUG: Start: Iteration 73
+2016-08-24 11:53:24,573 DEBUG: View 0 : 0.534591194969
+2016-08-24 11:53:24,581 DEBUG: View 1 : 0.522012578616
+2016-08-24 11:53:24,668 DEBUG: View 2 : 0.603773584906
+2016-08-24 11:53:24,676 DEBUG: View 3 : 0.522012578616
+2016-08-24 11:53:24,882 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:29,347 DEBUG: Start: Iteration 74
+2016-08-24 11:53:29,363 DEBUG: View 0 : 0.509433962264
+2016-08-24 11:53:29,371 DEBUG: View 1 : 0.345911949686
+2016-08-24 11:53:29,457 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:53:29,464 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:53:29,672 DEBUG: Best view : Clinic_
+2016-08-24 11:53:34,188 DEBUG: Start: Iteration 75
+2016-08-24 11:53:34,204 DEBUG: View 0 : 0.59748427673
+2016-08-24 11:53:34,212 DEBUG: View 1 : 0.51572327044
+2016-08-24 11:53:34,298 DEBUG: View 2 : 0.635220125786
+2016-08-24 11:53:34,306 DEBUG: View 3 : 0.48427672956
+2016-08-24 11:53:34,516 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:39,103 DEBUG: Start: Iteration 76
+2016-08-24 11:53:39,119 DEBUG: View 0 : 0.490566037736
+2016-08-24 11:53:39,127 DEBUG: View 1 : 0.584905660377
+2016-08-24 11:53:39,214 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:53:39,221 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:53:39,437 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:44,087 DEBUG: Start: Iteration 77
+2016-08-24 11:53:44,103 DEBUG: View 0 : 0.48427672956
+2016-08-24 11:53:44,111 DEBUG: View 1 : 0.320754716981
+2016-08-24 11:53:44,195 DEBUG: View 2 : 0.584905660377
+2016-08-24 11:53:44,202 DEBUG: View 3 : 0.654088050314
+2016-08-24 11:53:44,419 DEBUG: Best view : Clinic_
+2016-08-24 11:53:49,151 DEBUG: Start: Iteration 78
+2016-08-24 11:53:49,168 DEBUG: View 0 : 0.534591194969
+2016-08-24 11:53:49,175 DEBUG: View 1 : 0.540880503145
+2016-08-24 11:53:49,262 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:53:49,270 DEBUG: View 3 : 0.572327044025
+2016-08-24 11:53:49,487 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:54,269 DEBUG: Start: Iteration 79
+2016-08-24 11:53:54,285 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:53:54,293 DEBUG: View 1 : 0.509433962264
+2016-08-24 11:53:54,380 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:53:54,387 DEBUG: View 3 : 0.503144654088
+2016-08-24 11:53:54,609 DEBUG: Best view : RANSeq_
+2016-08-24 11:53:59,466 DEBUG: Start: Iteration 80
+2016-08-24 11:53:59,483 DEBUG: View 0 : 0.616352201258
+2016-08-24 11:53:59,491 DEBUG: View 1 : 0.672955974843
+2016-08-24 11:53:59,579 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:53:59,586 DEBUG: View 3 : 0.578616352201
+2016-08-24 11:53:59,807 DEBUG: Best view : MiRNA__
+2016-08-24 11:54:04,731 DEBUG: Start: Iteration 81
+2016-08-24 11:54:04,747 DEBUG: View 0 : 0.528301886792
+2016-08-24 11:54:04,755 DEBUG: View 1 : 0.704402515723
+2016-08-24 11:54:04,837 DEBUG: View 2 : 0.522012578616
+2016-08-24 11:54:04,845 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:54:05,067 DEBUG: Best view : MiRNA__
+2016-08-24 11:54:10,043 DEBUG: Start: Iteration 82
+2016-08-24 11:54:10,059 DEBUG: View 0 : 0.559748427673
+2016-08-24 11:54:10,067 DEBUG: View 1 : 0.440251572327
+2016-08-24 11:54:10,153 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:54:10,161 DEBUG: View 3 : 0.547169811321
+2016-08-24 11:54:10,387 DEBUG: Best view : RANSeq_
+2016-08-24 11:54:15,483 DEBUG: Start: Iteration 83
+2016-08-24 11:54:15,500 DEBUG: View 0 : 0.51572327044
+2016-08-24 11:54:15,507 DEBUG: View 1 : 0.477987421384
+2016-08-24 11:54:15,594 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:54:15,602 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:54:15,831 DEBUG: Best view : Clinic_
+2016-08-24 11:54:20,939 DEBUG: Start: Iteration 84
+2016-08-24 11:54:20,956 DEBUG: View 0 : 0.723270440252
+2016-08-24 11:54:20,964 DEBUG: View 1 : 0.408805031447
+2016-08-24 11:54:21,047 DEBUG: View 2 : 0.641509433962
+2016-08-24 11:54:21,054 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:54:21,285 DEBUG: Best view : Methyl_
+2016-08-24 11:54:26,440 DEBUG: Start: Iteration 85
+2016-08-24 11:54:26,456 DEBUG: View 0 : 0.427672955975
+2016-08-24 11:54:26,464 DEBUG: View 1 : 0.672955974843
+2016-08-24 11:54:26,552 DEBUG: View 2 : 0.616352201258
+2016-08-24 11:54:26,559 DEBUG: View 3 : 0.666666666667
+2016-08-24 11:54:26,790 DEBUG: Best view : Clinic_
+2016-08-24 11:54:32,015 DEBUG: Start: Iteration 86
+2016-08-24 11:54:32,031 DEBUG: View 0 : 0.540880503145
+2016-08-24 11:54:32,039 DEBUG: View 1 : 0.798742138365
+2016-08-24 11:54:32,114 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:54:32,121 DEBUG: View 3 : 0.496855345912
+2016-08-24 11:54:32,359 DEBUG: Best view : MiRNA__
+2016-08-24 11:54:37,638 DEBUG: Start: Iteration 87
+2016-08-24 11:54:37,654 DEBUG: View 0 : 0.553459119497
+2016-08-24 11:54:37,662 DEBUG: View 1 : 0.496855345912
+2016-08-24 11:54:37,748 DEBUG: View 2 : 0.654088050314
+2016-08-24 11:54:37,755 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:54:37,990 DEBUG: Best view : RANSeq_
+2016-08-24 11:54:43,338 DEBUG: Start: Iteration 88
+2016-08-24 11:54:43,355 DEBUG: View 0 : 0.40251572327
+2016-08-24 11:54:43,362 DEBUG: View 1 : 0.522012578616
+2016-08-24 11:54:43,453 DEBUG: View 2 : 0.578616352201
+2016-08-24 11:54:43,460 DEBUG: View 3 : 0.616352201258
+2016-08-24 11:54:43,698 DEBUG: Best view : Clinic_
+2016-08-24 11:54:49,088 DEBUG: Start: Iteration 89
+2016-08-24 11:54:49,105 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:54:49,112 DEBUG: View 1 : 0.377358490566
+2016-08-24 11:54:49,199 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:54:49,206 DEBUG: View 3 : 0.591194968553
+2016-08-24 11:54:49,450 DEBUG: Best view : RANSeq_
+2016-08-24 11:54:54,921 DEBUG: Start: Iteration 90
+2016-08-24 11:54:54,938 DEBUG: View 0 : 0.566037735849
+2016-08-24 11:54:54,946 DEBUG: View 1 : 0.710691823899
+2016-08-24 11:54:55,029 DEBUG: View 2 : 0.59748427673
+2016-08-24 11:54:55,037 DEBUG: View 3 : 0.540880503145
+2016-08-24 11:54:55,279 DEBUG: Best view : MiRNA__
+2016-08-24 11:55:00,796 DEBUG: Start: Iteration 91
+2016-08-24 11:55:00,812 DEBUG: View 0 : 0.59748427673
+2016-08-24 11:55:00,820 DEBUG: View 1 : 0.610062893082
+2016-08-24 11:55:00,908 DEBUG: View 2 : 0.584905660377
+2016-08-24 11:55:00,915 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:55:01,161 DEBUG: Best view : Clinic_
+2016-08-24 11:55:06,789 DEBUG: Start: Iteration 92
+2016-08-24 11:55:06,808 DEBUG: View 0 : 0.509433962264
+2016-08-24 11:55:06,816 DEBUG: View 1 : 0.345911949686
+2016-08-24 11:55:06,909 DEBUG: View 2 : 0.553459119497
+2016-08-24 11:55:06,916 DEBUG: View 3 : 0.51572327044
+2016-08-24 11:55:07,185 DEBUG: Best view : RANSeq_
+2016-08-24 11:55:12,930 DEBUG: Start: Iteration 93
+2016-08-24 11:55:12,947 DEBUG: View 0 : 0.62893081761
+2016-08-24 11:55:12,955 DEBUG: View 1 : 0.364779874214
+2016-08-24 11:55:13,040 DEBUG: View 2 : 0.534591194969
+2016-08-24 11:55:13,048 DEBUG: View 3 : 0.553459119497
+2016-08-24 11:55:13,301 DEBUG: Best view : Methyl_
+2016-08-24 11:55:19,024 DEBUG: Start: Iteration 94
+2016-08-24 11:55:19,040 DEBUG: View 0 : 0.452830188679
+2016-08-24 11:55:19,048 DEBUG: View 1 : 0.610062893082
+2016-08-24 11:55:19,137 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:55:19,144 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:55:19,395 DEBUG: Best view : MiRNA__
+2016-08-24 11:55:25,181 DEBUG: Start: Iteration 95
+2016-08-24 11:55:25,198 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:55:25,206 DEBUG: View 1 : 0.553459119497
+2016-08-24 11:55:25,288 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:55:25,296 DEBUG: View 3 : 0.584905660377
+2016-08-24 11:55:25,547 DEBUG: Best view : RANSeq_
+2016-08-24 11:55:31,382 DEBUG: Start: Iteration 96
+2016-08-24 11:55:31,399 DEBUG: View 0 : 0.522012578616
+2016-08-24 11:55:31,406 DEBUG: View 1 : 0.641509433962
+2016-08-24 11:55:31,493 DEBUG: View 2 : 0.559748427673
+2016-08-24 11:55:31,500 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:55:31,755 DEBUG: Best view : MiRNA__
+2016-08-24 11:55:37,653 DEBUG: Start: Iteration 97
+2016-08-24 11:55:37,669 DEBUG: View 0 : 0.522012578616
+2016-08-24 11:55:37,677 DEBUG: View 1 : 0.729559748428
+2016-08-24 11:55:37,760 DEBUG: View 2 : 0.566037735849
+2016-08-24 11:55:37,767 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:55:38,024 DEBUG: Best view : MiRNA__
+2016-08-24 11:55:43,967 DEBUG: Start: Iteration 98
+2016-08-24 11:55:43,984 DEBUG: View 0 : 0.471698113208
+2016-08-24 11:55:43,991 DEBUG: View 1 : 0.641509433962
+2016-08-24 11:55:44,074 DEBUG: View 2 : 0.635220125786
+2016-08-24 11:55:44,081 DEBUG: View 3 : 0.603773584906
+2016-08-24 11:55:44,341 DEBUG: Best view : RANSeq_
+2016-08-24 11:55:50,378 DEBUG: Start: Iteration 99
+2016-08-24 11:55:50,395 DEBUG: View 0 : 0.603773584906
+2016-08-24 11:55:50,402 DEBUG: View 1 : 0.459119496855
+2016-08-24 11:55:50,489 DEBUG: View 2 : 0.584905660377
+2016-08-24 11:55:50,497 DEBUG: View 3 : 0.522012578616
+2016-08-24 11:55:50,758 DEBUG: Best view : RANSeq_
+2016-08-24 11:55:56,848 DEBUG: Start: Iteration 100
+2016-08-24 11:55:56,864 DEBUG: View 0 : 0.540880503145
+2016-08-24 11:55:56,873 DEBUG: View 1 : 0.666666666667
+2016-08-24 11:55:56,961 DEBUG: View 2 : 0.654088050314
+2016-08-24 11:55:56,968 DEBUG: View 3 : 0.496855345912
+2016-08-24 11:55:57,232 DEBUG: Best view : RANSeq_
+2016-08-24 11:56:03,400 DEBUG: Start: Iteration 101
+2016-08-24 11:56:03,417 DEBUG: View 0 : 0.584905660377
+2016-08-24 11:56:03,424 DEBUG: View 1 : 0.415094339623
+2016-08-24 11:56:03,513 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:56:03,520 DEBUG: View 3 : 0.647798742138
+2016-08-24 11:56:03,784 DEBUG: Best view : Clinic_
+2016-08-24 11:56:10,265 DEBUG: Start: Iteration 102
+2016-08-24 11:56:10,292 DEBUG: View 0 : 0.547169811321
+2016-08-24 11:56:10,303 DEBUG: View 1 : 0.503144654088
+2016-08-24 11:56:10,405 DEBUG: View 2 : 0.62893081761
+2016-08-24 11:56:10,413 DEBUG: View 3 : 0.540880503145
+2016-08-24 11:56:10,685 DEBUG: Best view : RANSeq_
+2016-08-24 11:56:17,168 DEBUG: Start: Iteration 103
+2016-08-24 11:56:17,189 DEBUG: View 0 : 0.496855345912
+2016-08-24 11:56:17,198 DEBUG: View 1 : 0.377358490566
+2016-08-24 11:56:17,289 DEBUG: View 2 : 0.591194968553
+2016-08-24 11:56:17,297 DEBUG: View 3 : 0.62893081761
+2016-08-24 11:56:17,571 DEBUG: Best view : Clinic_
+2016-08-24 11:56:24,608 DEBUG: Start: Iteration 104
+2016-08-24 11:56:24,629 DEBUG: View 0 : 0.452830188679
+2016-08-24 11:56:24,642 DEBUG: View 1 : 0.528301886792
+2016-08-24 11:56:24,745 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:56:24,754 DEBUG: View 3 : 0.559748427673
+2016-08-24 11:56:25,049 DEBUG: Best view : RANSeq_
+2016-08-24 11:56:32,323 DEBUG: Start: Iteration 105
+2016-08-24 11:56:32,342 DEBUG: View 0 : 0.377358490566
+2016-08-24 11:56:32,353 DEBUG: View 1 : 0.647798742138
+2016-08-24 11:56:32,495 DEBUG: View 2 : 0.622641509434
+2016-08-24 11:56:32,509 DEBUG: View 3 : 0.540880503145
+2016-08-24 11:56:32,842 DEBUG: Best view : MiRNA__
+2016-08-24 11:56:40,165 DEBUG: Start: Iteration 106
+2016-08-24 11:56:40,186 DEBUG: View 0 : 0.490566037736
+2016-08-24 11:56:40,196 DEBUG: View 1 : 0.540880503145
+2016-08-24 11:56:40,286 DEBUG: View 2 : 0.51572327044
+2016-08-24 11:56:40,294 DEBUG: View 3 : 0.635220125786
+2016-08-24 11:56:40,572 DEBUG: Best view : Clinic_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-115712-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-115712-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..54ef5d1ed7293391eda4a4542da60e02641ad379
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-115712-CMultiV-Mumbo-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,4082 @@
+2016-08-24 11:57:12,454 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 11:57:12,454 INFO: Info: Labels used: No, Yes
+2016-08-24 11:57:12,455 INFO: Info: Length of dataset:347
+2016-08-24 11:57:12,456 INFO: ### Main Programm for Multiview Classification
+2016-08-24 11:57:12,456 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 11:57:12,457 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 11:57:12,457 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 11:57:12,457 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 11:57:12,458 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 11:57:12,458 INFO: Done: Read Database Files
+2016-08-24 11:57:12,458 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 11:57:12,462 INFO: Done: Determine validation split
+2016-08-24 11:57:12,462 INFO: Start: Determine 5 folds
+2016-08-24 11:57:12,469 INFO: Info: Length of Learning Sets: 196
+2016-08-24 11:57:12,469 INFO: Info: Length of Testing Sets: 48
+2016-08-24 11:57:12,469 INFO: Info: Length of Validation Set: 103
+2016-08-24 11:57:12,469 INFO: Done: Determine folds
+2016-08-24 11:57:12,470 INFO: Start: Learning with Mumbo and 5 folds
+2016-08-24 11:57:12,470 INFO: Start: Fold number 1
+2016-08-24 11:57:14,621 DEBUG: Start: Iteration 1
+2016-08-24 11:57:14,642 DEBUG: View 0 : 0.379146919431
+2016-08-24 11:57:14,652 DEBUG: View 1 : 0.620853080569
+2016-08-24 11:57:14,779 DEBUG: View 2 : 0.488151658768
+2016-08-24 11:57:14,789 DEBUG: View 3 : 0.620853080569
+2016-08-24 11:57:14,848 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:14,947 DEBUG: Start: Iteration 2
+2016-08-24 11:57:14,970 DEBUG: View 0 : 0.625592417062
+2016-08-24 11:57:14,983 DEBUG: View 1 : 0.63981042654
+2016-08-24 11:57:15,114 DEBUG: View 2 : 0.658767772512
+2016-08-24 11:57:15,124 DEBUG: View 3 : 0.568720379147
+2016-08-24 11:57:15,196 DEBUG: Best view : RANSeq_
+2016-08-24 11:57:15,401 DEBUG: Start: Iteration 3
+2016-08-24 11:57:15,424 DEBUG: View 0 : 0.611374407583
+2016-08-24 11:57:15,437 DEBUG: View 1 : 0.450236966825
+2016-08-24 11:57:15,556 DEBUG: View 2 : 0.592417061611
+2016-08-24 11:57:15,566 DEBUG: View 3 : 0.563981042654
+2016-08-24 11:57:15,641 DEBUG: Best view : Methyl_
+2016-08-24 11:57:15,925 DEBUG: Start: Iteration 4
+2016-08-24 11:57:15,946 DEBUG: View 0 : 0.54028436019
+2016-08-24 11:57:15,958 DEBUG: View 1 : 0.630331753555
+2016-08-24 11:57:16,076 DEBUG: View 2 : 0.502369668246
+2016-08-24 11:57:16,085 DEBUG: View 3 : 0.625592417062
+2016-08-24 11:57:16,162 DEBUG: Best view : Clinic_
+2016-08-24 11:57:16,517 DEBUG: Start: Iteration 5
+2016-08-24 11:57:16,539 DEBUG: View 0 : 0.682464454976
+2016-08-24 11:57:16,551 DEBUG: View 1 : 0.720379146919
+2016-08-24 11:57:16,674 DEBUG: View 2 : 0.54028436019
+2016-08-24 11:57:16,684 DEBUG: View 3 : 0.57345971564
+2016-08-24 11:57:16,763 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:17,203 DEBUG: Start: Iteration 6
+2016-08-24 11:57:17,226 DEBUG: View 0 : 0.521327014218
+2016-08-24 11:57:17,238 DEBUG: View 1 : 0.715639810427
+2016-08-24 11:57:17,363 DEBUG: View 2 : 0.630331753555
+2016-08-24 11:57:17,372 DEBUG: View 3 : 0.644549763033
+2016-08-24 11:57:17,454 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:17,964 DEBUG: Start: Iteration 7
+2016-08-24 11:57:17,985 DEBUG: View 0 : 0.559241706161
+2016-08-24 11:57:17,997 DEBUG: View 1 : 0.398104265403
+2016-08-24 11:57:18,113 DEBUG: View 2 : 0.440758293839
+2016-08-24 11:57:18,123 DEBUG: View 3 : 0.715639810427
+2016-08-24 11:57:18,206 DEBUG: Best view : Clinic_
+2016-08-24 11:57:18,799 DEBUG: Start: Iteration 8
+2016-08-24 11:57:18,821 DEBUG: View 0 : 0.497630331754
+2016-08-24 11:57:18,833 DEBUG: View 1 : 0.502369668246
+2016-08-24 11:57:18,946 DEBUG: View 2 : 0.488151658768
+2016-08-24 11:57:18,955 DEBUG: View 3 : 0.654028436019
+2016-08-24 11:57:19,042 DEBUG: Best view : Clinic_
+2016-08-24 11:57:19,704 DEBUG: Start: Iteration 9
+2016-08-24 11:57:19,726 DEBUG: View 0 : 0.511848341232
+2016-08-24 11:57:19,736 DEBUG: View 1 : 0.635071090047
+2016-08-24 11:57:19,856 DEBUG: View 2 : 0.568720379147
+2016-08-24 11:57:19,866 DEBUG: View 3 : 0.687203791469
+2016-08-24 11:57:19,955 DEBUG: Best view : Clinic_
+2016-08-24 11:57:20,697 DEBUG: Start: Iteration 10
+2016-08-24 11:57:20,718 DEBUG: View 0 : 0.616113744076
+2016-08-24 11:57:20,730 DEBUG: View 1 : 0.630331753555
+2016-08-24 11:57:20,848 DEBUG: View 2 : 0.559241706161
+2016-08-24 11:57:20,857 DEBUG: View 3 : 0.597156398104
+2016-08-24 11:57:20,950 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:21,773 DEBUG: Start: Iteration 11
+2016-08-24 11:57:21,795 DEBUG: View 0 : 0.379146919431
+2016-08-24 11:57:21,806 DEBUG: View 1 : 0.450236966825
+2016-08-24 11:57:21,923 DEBUG: View 2 : 0.554502369668
+2016-08-24 11:57:21,932 DEBUG: View 3 : 0.545023696682
+2016-08-24 11:57:22,027 DEBUG: Best view : Clinic_
+2016-08-24 11:57:22,922 DEBUG: Start: Iteration 12
+2016-08-24 11:57:22,944 DEBUG: View 0 : 0.601895734597
+2016-08-24 11:57:22,955 DEBUG: View 1 : 0.663507109005
+2016-08-24 11:57:23,071 DEBUG: View 2 : 0.563981042654
+2016-08-24 11:57:23,081 DEBUG: View 3 : 0.611374407583
+2016-08-24 11:57:23,178 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:24,152 DEBUG: Start: Iteration 13
+2016-08-24 11:57:24,174 DEBUG: View 0 : 0.473933649289
+2016-08-24 11:57:24,185 DEBUG: View 1 : 0.682464454976
+2016-08-24 11:57:24,301 DEBUG: View 2 : 0.611374407583
+2016-08-24 11:57:24,311 DEBUG: View 3 : 0.60663507109
+2016-08-24 11:57:24,411 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:25,461 DEBUG: Start: Iteration 14
+2016-08-24 11:57:25,482 DEBUG: View 0 : 0.630331753555
+2016-08-24 11:57:25,493 DEBUG: View 1 : 0.644549763033
+2016-08-24 11:57:25,610 DEBUG: View 2 : 0.60663507109
+2016-08-24 11:57:25,619 DEBUG: View 3 : 0.530805687204
+2016-08-24 11:57:25,722 DEBUG: Best view : Methyl_
+2016-08-24 11:57:26,857 DEBUG: Start: Iteration 15
+2016-08-24 11:57:26,878 DEBUG: View 0 : 0.502369668246
+2016-08-24 11:57:26,889 DEBUG: View 1 : 0.592417061611
+2016-08-24 11:57:27,009 DEBUG: View 2 : 0.578199052133
+2016-08-24 11:57:27,019 DEBUG: View 3 : 0.530805687204
+2016-08-24 11:57:27,123 DEBUG: Best view : RANSeq_
+2016-08-24 11:57:28,347 DEBUG: Start: Iteration 16
+2016-08-24 11:57:28,368 DEBUG: View 0 : 0.454976303318
+2016-08-24 11:57:28,379 DEBUG: View 1 : 0.535545023697
+2016-08-24 11:57:28,499 DEBUG: View 2 : 0.54028436019
+2016-08-24 11:57:28,509 DEBUG: View 3 : 0.668246445498
+2016-08-24 11:57:28,617 DEBUG: Best view : Clinic_
+2016-08-24 11:57:29,920 DEBUG: Start: Iteration 17
+2016-08-24 11:57:29,941 DEBUG: View 0 : 0.587677725118
+2016-08-24 11:57:29,952 DEBUG: View 1 : 0.511848341232
+2016-08-24 11:57:30,072 DEBUG: View 2 : 0.611374407583
+2016-08-24 11:57:30,081 DEBUG: View 3 : 0.601895734597
+2016-08-24 11:57:30,193 DEBUG: Best view : Clinic_
+2016-08-24 11:57:31,573 DEBUG: Start: Iteration 18
+2016-08-24 11:57:31,594 DEBUG: View 0 : 0.502369668246
+2016-08-24 11:57:31,605 DEBUG: View 1 : 0.682464454976
+2016-08-24 11:57:31,723 DEBUG: View 2 : 0.516587677725
+2016-08-24 11:57:31,732 DEBUG: View 3 : 0.587677725118
+2016-08-24 11:57:31,846 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:33,303 DEBUG: Start: Iteration 19
+2016-08-24 11:57:33,324 DEBUG: View 0 : 0.60663507109
+2016-08-24 11:57:33,335 DEBUG: View 1 : 0.663507109005
+2016-08-24 11:57:33,455 DEBUG: View 2 : 0.454976303318
+2016-08-24 11:57:33,465 DEBUG: View 3 : 0.663507109005
+2016-08-24 11:57:33,582 DEBUG: Best view : Clinic_
+2016-08-24 11:57:35,115 DEBUG: Start: Iteration 20
+2016-08-24 11:57:35,137 DEBUG: View 0 : 0.658767772512
+2016-08-24 11:57:35,148 DEBUG: View 1 : 0.644549763033
+2016-08-24 11:57:35,256 DEBUG: View 2 : 0.630331753555
+2016-08-24 11:57:35,266 DEBUG: View 3 : 0.616113744076
+2016-08-24 11:57:35,390 DEBUG: Best view : Methyl_
+2016-08-24 11:57:37,005 DEBUG: Start: Iteration 21
+2016-08-24 11:57:37,026 DEBUG: View 0 : 0.60663507109
+2016-08-24 11:57:37,037 DEBUG: View 1 : 0.644549763033
+2016-08-24 11:57:37,153 DEBUG: View 2 : 0.582938388626
+2016-08-24 11:57:37,162 DEBUG: View 3 : 0.672985781991
+2016-08-24 11:57:37,285 DEBUG: Best view : Clinic_
+2016-08-24 11:57:38,978 DEBUG: Start: Iteration 22
+2016-08-24 11:57:38,999 DEBUG: View 0 : 0.658767772512
+2016-08-24 11:57:39,010 DEBUG: View 1 : 0.473933649289
+2016-08-24 11:57:39,131 DEBUG: View 2 : 0.601895734597
+2016-08-24 11:57:39,140 DEBUG: View 3 : 0.559241706161
+2016-08-24 11:57:39,265 DEBUG: Best view : Methyl_
+2016-08-24 11:57:41,041 DEBUG: Start: Iteration 23
+2016-08-24 11:57:41,063 DEBUG: View 0 : 0.630331753555
+2016-08-24 11:57:41,073 DEBUG: View 1 : 0.492890995261
+2016-08-24 11:57:41,179 DEBUG: View 2 : 0.592417061611
+2016-08-24 11:57:41,188 DEBUG: View 3 : 0.682464454976
+2016-08-24 11:57:41,317 DEBUG: Best view : Clinic_
+2016-08-24 11:57:43,177 DEBUG: Start: Iteration 24
+2016-08-24 11:57:43,198 DEBUG: View 0 : 0.417061611374
+2016-08-24 11:57:43,208 DEBUG: View 1 : 0.663507109005
+2016-08-24 11:57:43,329 DEBUG: View 2 : 0.57345971564
+2016-08-24 11:57:43,338 DEBUG: View 3 : 0.57345971564
+2016-08-24 11:57:43,468 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:45,397 DEBUG: Start: Iteration 25
+2016-08-24 11:57:45,418 DEBUG: View 0 : 0.630331753555
+2016-08-24 11:57:45,428 DEBUG: View 1 : 0.388625592417
+2016-08-24 11:57:45,549 DEBUG: View 2 : 0.568720379147
+2016-08-24 11:57:45,558 DEBUG: View 3 : 0.63981042654
+2016-08-24 11:57:45,690 DEBUG: Best view : Clinic_
+2016-08-24 11:57:47,697 DEBUG: Start: Iteration 26
+2016-08-24 11:57:47,718 DEBUG: View 0 : 0.701421800948
+2016-08-24 11:57:47,727 DEBUG: View 1 : 0.388625592417
+2016-08-24 11:57:47,849 DEBUG: View 2 : 0.545023696682
+2016-08-24 11:57:47,859 DEBUG: View 3 : 0.616113744076
+2016-08-24 11:57:47,994 DEBUG: Best view : Methyl_
+2016-08-24 11:57:50,081 DEBUG: Start: Iteration 27
+2016-08-24 11:57:50,102 DEBUG: View 0 : 0.521327014218
+2016-08-24 11:57:50,112 DEBUG: View 1 : 0.744075829384
+2016-08-24 11:57:50,232 DEBUG: View 2 : 0.535545023697
+2016-08-24 11:57:50,241 DEBUG: View 3 : 0.611374407583
+2016-08-24 11:57:50,382 DEBUG: Best view : MiRNA__
+2016-08-24 11:57:52,548 DEBUG: Start: Iteration 28
+2016-08-24 11:57:52,569 DEBUG: View 0 : 0.725118483412
+2016-08-24 11:57:52,579 DEBUG: View 1 : 0.478672985782
+2016-08-24 11:57:52,696 DEBUG: View 2 : 0.473933649289
+2016-08-24 11:57:52,705 DEBUG: View 3 : 0.57345971564
+2016-08-24 11:57:52,847 DEBUG: Best view : Methyl_
+2016-08-24 11:57:55,093 DEBUG: Start: Iteration 29
+2016-08-24 11:57:55,114 DEBUG: View 0 : 0.473933649289
+2016-08-24 11:57:55,124 DEBUG: View 1 : 0.611374407583
+2016-08-24 11:57:55,243 DEBUG: View 2 : 0.587677725118
+2016-08-24 11:57:55,253 DEBUG: View 3 : 0.587677725118
+2016-08-24 11:57:55,398 DEBUG: Best view : Clinic_
+2016-08-24 11:57:57,716 DEBUG: Start: Iteration 30
+2016-08-24 11:57:57,737 DEBUG: View 0 : 0.516587677725
+2016-08-24 11:57:57,747 DEBUG: View 1 : 0.582938388626
+2016-08-24 11:57:57,864 DEBUG: View 2 : 0.625592417062
+2016-08-24 11:57:57,873 DEBUG: View 3 : 0.592417061611
+2016-08-24 11:57:58,023 DEBUG: Best view : RANSeq_
+2016-08-24 11:58:00,451 DEBUG: Start: Iteration 31
+2016-08-24 11:58:00,472 DEBUG: View 0 : 0.488151658768
+2016-08-24 11:58:00,482 DEBUG: View 1 : 0.677725118483
+2016-08-24 11:58:00,594 DEBUG: View 2 : 0.554502369668
+2016-08-24 11:58:00,604 DEBUG: View 3 : 0.530805687204
+2016-08-24 11:58:00,755 DEBUG: Best view : MiRNA__
+2016-08-24 11:58:03,265 DEBUG: Start: Iteration 32
+2016-08-24 11:58:03,287 DEBUG: View 0 : 0.507109004739
+2016-08-24 11:58:03,296 DEBUG: View 1 : 0.559241706161
+2016-08-24 11:58:03,410 DEBUG: View 2 : 0.587677725118
+2016-08-24 11:58:03,419 DEBUG: View 3 : 0.687203791469
+2016-08-24 11:58:03,573 DEBUG: Best view : Clinic_
+2016-08-24 11:58:06,148 DEBUG: Start: Iteration 33
+2016-08-24 11:58:06,168 DEBUG: View 0 : 0.545023696682
+2016-08-24 11:58:06,179 DEBUG: View 1 : 0.54028436019
+2016-08-24 11:58:06,300 DEBUG: View 2 : 0.644549763033
+2016-08-24 11:58:06,310 DEBUG: View 3 : 0.597156398104
+2016-08-24 11:58:06,465 DEBUG: Best view : RANSeq_
+2016-08-24 11:58:09,133 DEBUG: Start: Iteration 34
+2016-08-24 11:58:09,155 DEBUG: View 0 : 0.549763033175
+2016-08-24 11:58:09,164 DEBUG: View 1 : 0.407582938389
+2016-08-24 11:58:09,283 DEBUG: View 2 : 0.54028436019
+2016-08-24 11:58:09,292 DEBUG: View 3 : 0.507109004739
+2016-08-24 11:58:09,450 DEBUG: Best view : RANSeq_
+2016-08-24 11:58:12,216 DEBUG: Start: Iteration 35
+2016-08-24 11:58:12,237 DEBUG: View 0 : 0.582938388626
+2016-08-24 11:58:12,247 DEBUG: View 1 : 0.611374407583
+2016-08-24 11:58:12,360 DEBUG: View 2 : 0.559241706161
+2016-08-24 11:58:12,369 DEBUG: View 3 : 0.611374407583
+2016-08-24 11:58:12,530 DEBUG: Best view : Clinic_
+2016-08-24 11:58:15,378 DEBUG: Start: Iteration 36
+2016-08-24 11:58:15,399 DEBUG: View 0 : 0.473933649289
+2016-08-24 11:58:15,408 DEBUG: View 1 : 0.492890995261
+2016-08-24 11:58:15,522 DEBUG: View 2 : 0.635071090047
+2016-08-24 11:58:15,532 DEBUG: View 3 : 0.530805687204
+2016-08-24 11:58:15,696 DEBUG: Best view : RANSeq_
+2016-08-24 11:58:18,642 DEBUG: Start: Iteration 37
+2016-08-24 11:58:18,663 DEBUG: View 0 : 0.559241706161
+2016-08-24 11:58:18,673 DEBUG: View 1 : 0.511848341232
+2016-08-24 11:58:18,794 DEBUG: View 2 : 0.592417061611
+2016-08-24 11:58:18,803 DEBUG: View 3 : 0.545023696682
+2016-08-24 11:58:18,971 DEBUG: Best view : RANSeq_
+2016-08-24 11:58:22,000 DEBUG: Start: Iteration 38
+2016-08-24 11:58:22,021 DEBUG: View 0 : 0.549763033175
+2016-08-24 11:58:22,031 DEBUG: View 1 : 0.654028436019
+2016-08-24 11:58:22,156 DEBUG: View 2 : 0.549763033175
+2016-08-24 11:58:22,165 DEBUG: View 3 : 0.42654028436
+2016-08-24 11:58:22,335 DEBUG: Best view : MiRNA__
+2016-08-24 11:58:25,444 DEBUG: Start: Iteration 39
+2016-08-24 11:58:25,465 DEBUG: View 0 : 0.635071090047
+2016-08-24 11:58:25,475 DEBUG: View 1 : 0.838862559242
+2016-08-24 11:58:25,592 DEBUG: View 2 : 0.554502369668
+2016-08-24 11:58:25,601 DEBUG: View 3 : 0.526066350711
+2016-08-24 11:58:25,773 DEBUG: Best view : MiRNA__
+2016-08-24 11:58:28,956 DEBUG: Start: Iteration 40
+2016-08-24 11:58:28,978 DEBUG: View 0 : 0.421800947867
+2016-08-24 11:58:28,988 DEBUG: View 1 : 0.545023696682
+2016-08-24 11:58:29,112 DEBUG: View 2 : 0.568720379147
+2016-08-24 11:58:29,121 DEBUG: View 3 : 0.578199052133
+2016-08-24 11:58:29,297 DEBUG: Best view : Clinic_
+2016-08-24 11:58:32,559 DEBUG: Start: Iteration 41
+2016-08-24 11:58:32,580 DEBUG: View 0 : 0.559241706161
+2016-08-24 11:58:32,589 DEBUG: View 1 : 0.464454976303
+2016-08-24 11:58:32,706 DEBUG: View 2 : 0.601895734597
+2016-08-24 11:58:32,715 DEBUG: View 3 : 0.630331753555
+2016-08-24 11:58:32,893 DEBUG: Best view : Clinic_
+2016-08-24 11:58:36,238 DEBUG: Start: Iteration 42
+2016-08-24 11:58:36,259 DEBUG: View 0 : 0.54028436019
+2016-08-24 11:58:36,269 DEBUG: View 1 : 0.492890995261
+2016-08-24 11:58:36,391 DEBUG: View 2 : 0.563981042654
+2016-08-24 11:58:36,400 DEBUG: View 3 : 0.611374407583
+2016-08-24 11:58:36,581 DEBUG: Best view : Clinic_
+2016-08-24 11:58:40,001 DEBUG: Start: Iteration 43
+2016-08-24 11:58:40,022 DEBUG: View 0 : 0.511848341232
+2016-08-24 11:58:40,032 DEBUG: View 1 : 0.60663507109
+2016-08-24 11:58:40,150 DEBUG: View 2 : 0.57345971564
+2016-08-24 11:58:40,159 DEBUG: View 3 : 0.644549763033
+2016-08-24 11:58:40,346 DEBUG: Best view : Clinic_
+2016-08-24 11:58:43,845 DEBUG: Start: Iteration 44
+2016-08-24 11:58:43,866 DEBUG: View 0 : 0.63981042654
+2016-08-24 11:58:43,876 DEBUG: View 1 : 0.521327014218
+2016-08-24 11:58:43,997 DEBUG: View 2 : 0.568720379147
+2016-08-24 11:58:44,007 DEBUG: View 3 : 0.563981042654
+2016-08-24 11:58:44,194 DEBUG: Best view : Methyl_
+2016-08-24 11:58:47,769 DEBUG: Start: Iteration 45
+2016-08-24 11:58:47,790 DEBUG: View 0 : 0.597156398104
+2016-08-24 11:58:47,800 DEBUG: View 1 : 0.417061611374
+2016-08-24 11:58:47,921 DEBUG: View 2 : 0.635071090047
+2016-08-24 11:58:47,931 DEBUG: View 3 : 0.554502369668
+2016-08-24 11:58:48,122 DEBUG: Best view : RANSeq_
+2016-08-24 11:58:51,801 DEBUG: Start: Iteration 46
+2016-08-24 11:58:51,822 DEBUG: View 0 : 0.767772511848
+2016-08-24 11:58:51,832 DEBUG: View 1 : 0.516587677725
+2016-08-24 11:58:51,953 DEBUG: View 2 : 0.587677725118
+2016-08-24 11:58:51,962 DEBUG: View 3 : 0.511848341232
+2016-08-24 11:58:52,156 DEBUG: Best view : Methyl_
+2016-08-24 11:58:55,936 DEBUG: Start: Iteration 47
+2016-08-24 11:58:55,957 DEBUG: View 0 : 0.601895734597
+2016-08-24 11:58:55,967 DEBUG: View 1 : 0.663507109005
+2016-08-24 11:58:56,088 DEBUG: View 2 : 0.492890995261
+2016-08-24 11:58:56,097 DEBUG: View 3 : 0.578199052133
+2016-08-24 11:58:56,294 DEBUG: Best view : MiRNA__
+2016-08-24 11:59:00,122 DEBUG: Start: Iteration 48
+2016-08-24 11:59:00,144 DEBUG: View 0 : 0.57345971564
+2016-08-24 11:59:00,153 DEBUG: View 1 : 0.535545023697
+2016-08-24 11:59:00,265 DEBUG: View 2 : 0.582938388626
+2016-08-24 11:59:00,274 DEBUG: View 3 : 0.63981042654
+2016-08-24 11:59:00,473 DEBUG: Best view : Clinic_
+2016-08-24 11:59:04,401 DEBUG: Start: Iteration 49
+2016-08-24 11:59:04,422 DEBUG: View 0 : 0.587677725118
+2016-08-24 11:59:04,432 DEBUG: View 1 : 0.511848341232
+2016-08-24 11:59:04,563 DEBUG: View 2 : 0.545023696682
+2016-08-24 11:59:04,573 DEBUG: View 3 : 0.668246445498
+2016-08-24 11:59:04,783 DEBUG: Best view : Clinic_
+2016-08-24 11:59:08,788 DEBUG: Start: Iteration 50
+2016-08-24 11:59:08,810 DEBUG: View 0 : 0.578199052133
+2016-08-24 11:59:08,819 DEBUG: View 1 : 0.317535545024
+2016-08-24 11:59:08,939 DEBUG: View 2 : 0.587677725118
+2016-08-24 11:59:08,948 DEBUG: View 3 : 0.511848341232
+2016-08-24 11:59:09,155 DEBUG: Best view : RANSeq_
+2016-08-24 11:59:13,226 DEBUG: Start: Iteration 51
+2016-08-24 11:59:13,247 DEBUG: View 0 : 0.559241706161
+2016-08-24 11:59:13,257 DEBUG: View 1 : 0.526066350711
+2016-08-24 11:59:13,375 DEBUG: View 2 : 0.545023696682
+2016-08-24 11:59:13,384 DEBUG: View 3 : 0.530805687204
+2016-08-24 11:59:13,595 DEBUG: Best view : RANSeq_
+2016-08-24 11:59:17,767 DEBUG: Start: Iteration 52
+2016-08-24 11:59:17,788 DEBUG: View 0 : 0.549763033175
+2016-08-24 11:59:17,798 DEBUG: View 1 : 0.488151658768
+2016-08-24 11:59:17,910 DEBUG: View 2 : 0.611374407583
+2016-08-24 11:59:17,919 DEBUG: View 3 : 0.578199052133
+2016-08-24 11:59:18,133 DEBUG: Best view : RANSeq_
+2016-08-24 11:59:22,394 DEBUG: Start: Iteration 53
+2016-08-24 11:59:22,415 DEBUG: View 0 : 0.492890995261
+2016-08-24 11:59:22,425 DEBUG: View 1 : 0.582938388626
+2016-08-24 11:59:22,545 DEBUG: View 2 : 0.649289099526
+2016-08-24 11:59:22,555 DEBUG: View 3 : 0.663507109005
+2016-08-24 11:59:22,768 DEBUG: Best view : Clinic_
+2016-08-24 11:59:27,110 DEBUG: Start: Iteration 54
+2016-08-24 11:59:27,131 DEBUG: View 0 : 0.554502369668
+2016-08-24 11:59:27,141 DEBUG: View 1 : 0.620853080569
+2016-08-24 11:59:27,262 DEBUG: View 2 : 0.60663507109
+2016-08-24 11:59:27,272 DEBUG: View 3 : 0.630331753555
+2016-08-24 11:59:27,488 DEBUG: Best view : Clinic_
+2016-08-24 11:59:31,904 DEBUG: Start: Iteration 55
+2016-08-24 11:59:31,925 DEBUG: View 0 : 0.592417061611
+2016-08-24 11:59:31,935 DEBUG: View 1 : 0.436018957346
+2016-08-24 11:59:32,054 DEBUG: View 2 : 0.60663507109
+2016-08-24 11:59:32,064 DEBUG: View 3 : 0.554502369668
+2016-08-24 11:59:32,283 DEBUG: Best view : RANSeq_
+2016-08-24 11:59:36,798 DEBUG: Start: Iteration 56
+2016-08-24 11:59:36,819 DEBUG: View 0 : 0.616113744076
+2016-08-24 11:59:36,829 DEBUG: View 1 : 0.383886255924
+2016-08-24 11:59:36,947 DEBUG: View 2 : 0.559241706161
+2016-08-24 11:59:36,956 DEBUG: View 3 : 0.658767772512
+2016-08-24 11:59:37,178 DEBUG: Best view : Clinic_
+2016-08-24 11:59:41,766 DEBUG: Start: Iteration 57
+2016-08-24 11:59:41,787 DEBUG: View 0 : 0.559241706161
+2016-08-24 11:59:41,796 DEBUG: View 1 : 0.592417061611
+2016-08-24 11:59:41,913 DEBUG: View 2 : 0.587677725118
+2016-08-24 11:59:41,922 DEBUG: View 3 : 0.582938388626
+2016-08-24 11:59:42,148 DEBUG: Best view : Clinic_
+2016-08-24 11:59:46,820 DEBUG: Start: Iteration 58
+2016-08-24 11:59:46,841 DEBUG: View 0 : 0.57345971564
+2016-08-24 11:59:46,851 DEBUG: View 1 : 0.478672985782
+2016-08-24 11:59:46,973 DEBUG: View 2 : 0.563981042654
+2016-08-24 11:59:46,982 DEBUG: View 3 : 0.630331753555
+2016-08-24 11:59:47,211 DEBUG: Best view : Clinic_
+2016-08-24 11:59:51,954 DEBUG: Start: Iteration 59
+2016-08-24 11:59:51,975 DEBUG: View 0 : 0.582938388626
+2016-08-24 11:59:51,985 DEBUG: View 1 : 0.625592417062
+2016-08-24 11:59:52,105 DEBUG: View 2 : 0.592417061611
+2016-08-24 11:59:52,115 DEBUG: View 3 : 0.464454976303
+2016-08-24 11:59:52,344 DEBUG: Best view : MiRNA__
+2016-08-24 11:59:57,158 DEBUG: Start: Iteration 60
+2016-08-24 11:59:57,179 DEBUG: View 0 : 0.644549763033
+2016-08-24 11:59:57,189 DEBUG: View 1 : 0.582938388626
+2016-08-24 11:59:57,305 DEBUG: View 2 : 0.530805687204
+2016-08-24 11:59:57,314 DEBUG: View 3 : 0.521327014218
+2016-08-24 11:59:57,548 DEBUG: Best view : Methyl_
+2016-08-24 12:00:02,454 DEBUG: Start: Iteration 61
+2016-08-24 12:00:02,476 DEBUG: View 0 : 0.492890995261
+2016-08-24 12:00:02,485 DEBUG: View 1 : 0.545023696682
+2016-08-24 12:00:02,603 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:00:02,613 DEBUG: View 3 : 0.549763033175
+2016-08-24 12:00:02,847 DEBUG: Best view : RANSeq_
+2016-08-24 12:00:07,853 DEBUG: Start: Iteration 62
+2016-08-24 12:00:07,875 DEBUG: View 0 : 0.388625592417
+2016-08-24 12:00:07,885 DEBUG: View 1 : 0.691943127962
+2016-08-24 12:00:08,001 DEBUG: View 2 : 0.63981042654
+2016-08-24 12:00:08,011 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:00:08,248 DEBUG: Best view : MiRNA__
+2016-08-24 12:00:13,319 DEBUG: Start: Iteration 63
+2016-08-24 12:00:13,340 DEBUG: View 0 : 0.563981042654
+2016-08-24 12:00:13,350 DEBUG: View 1 : 0.63981042654
+2016-08-24 12:00:13,468 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:00:13,478 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:00:13,717 DEBUG: Best view : MiRNA__
+2016-08-24 12:00:18,868 DEBUG: Start: Iteration 64
+2016-08-24 12:00:18,889 DEBUG: View 0 : 0.492890995261
+2016-08-24 12:00:18,899 DEBUG: View 1 : 0.559241706161
+2016-08-24 12:00:19,016 DEBUG: View 2 : 0.473933649289
+2016-08-24 12:00:19,025 DEBUG: View 3 : 0.715639810427
+2016-08-24 12:00:19,268 DEBUG: Best view : Clinic_
+2016-08-24 12:00:24,514 DEBUG: Start: Iteration 65
+2016-08-24 12:00:24,535 DEBUG: View 0 : 0.526066350711
+2016-08-24 12:00:24,545 DEBUG: View 1 : 0.668246445498
+2016-08-24 12:00:24,657 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:00:24,667 DEBUG: View 3 : 0.654028436019
+2016-08-24 12:00:24,914 DEBUG: Best view : Clinic_
+2016-08-24 12:00:30,236 DEBUG: Start: Iteration 66
+2016-08-24 12:00:30,257 DEBUG: View 0 : 0.649289099526
+2016-08-24 12:00:30,267 DEBUG: View 1 : 0.421800947867
+2016-08-24 12:00:30,388 DEBUG: View 2 : 0.611374407583
+2016-08-24 12:00:30,397 DEBUG: View 3 : 0.473933649289
+2016-08-24 12:00:30,649 DEBUG: Best view : Methyl_
+2016-08-24 12:00:36,037 DEBUG: Start: Iteration 67
+2016-08-24 12:00:36,058 DEBUG: View 0 : 0.644549763033
+2016-08-24 12:00:36,068 DEBUG: View 1 : 0.668246445498
+2016-08-24 12:00:36,184 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:00:36,193 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:00:36,445 DEBUG: Best view : MiRNA__
+2016-08-24 12:00:41,924 DEBUG: Start: Iteration 68
+2016-08-24 12:00:41,945 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:00:41,955 DEBUG: View 1 : 0.649289099526
+2016-08-24 12:00:42,071 DEBUG: View 2 : 0.57345971564
+2016-08-24 12:00:42,080 DEBUG: View 3 : 0.60663507109
+2016-08-24 12:00:42,335 DEBUG: Best view : MiRNA__
+2016-08-24 12:00:47,885 DEBUG: Start: Iteration 69
+2016-08-24 12:00:47,907 DEBUG: View 0 : 0.45971563981
+2016-08-24 12:00:47,916 DEBUG: View 1 : 0.706161137441
+2016-08-24 12:00:48,034 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:00:48,043 DEBUG: View 3 : 0.672985781991
+2016-08-24 12:00:48,301 DEBUG: Best view : MiRNA__
+2016-08-24 12:00:53,925 DEBUG: Start: Iteration 70
+2016-08-24 12:00:53,946 DEBUG: View 0 : 0.587677725118
+2016-08-24 12:00:53,955 DEBUG: View 1 : 0.60663507109
+2016-08-24 12:00:54,077 DEBUG: View 2 : 0.654028436019
+2016-08-24 12:00:54,086 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:00:54,348 DEBUG: Best view : RANSeq_
+2016-08-24 12:01:00,090 DEBUG: Start: Iteration 71
+2016-08-24 12:01:00,111 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:01:00,121 DEBUG: View 1 : 0.729857819905
+2016-08-24 12:01:00,238 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:01:00,247 DEBUG: View 3 : 0.687203791469
+2016-08-24 12:01:00,509 DEBUG: Best view : MiRNA__
+2016-08-24 12:01:06,310 DEBUG: Start: Iteration 72
+2016-08-24 12:01:06,331 DEBUG: View 0 : 0.630331753555
+2016-08-24 12:01:06,341 DEBUG: View 1 : 0.388625592417
+2016-08-24 12:01:06,454 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:01:06,463 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:01:06,728 DEBUG: Best view : Methyl_
+2016-08-24 12:01:12,616 DEBUG: Start: Iteration 73
+2016-08-24 12:01:12,637 DEBUG: View 0 : 0.701421800948
+2016-08-24 12:01:12,647 DEBUG: View 1 : 0.691943127962
+2016-08-24 12:01:12,765 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:01:12,774 DEBUG: View 3 : 0.710900473934
+2016-08-24 12:01:13,045 DEBUG: Best view : Clinic_
+2016-08-24 12:01:19,004 DEBUG: Start: Iteration 74
+2016-08-24 12:01:19,025 DEBUG: View 0 : 0.578199052133
+2016-08-24 12:01:19,035 DEBUG: View 1 : 0.559241706161
+2016-08-24 12:01:19,156 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:01:19,165 DEBUG: View 3 : 0.677725118483
+2016-08-24 12:01:19,437 DEBUG: Best view : Clinic_
+2016-08-24 12:01:25,474 DEBUG: Start: Iteration 75
+2016-08-24 12:01:25,495 DEBUG: View 0 : 0.601895734597
+2016-08-24 12:01:25,505 DEBUG: View 1 : 0.649289099526
+2016-08-24 12:01:25,617 DEBUG: View 2 : 0.549763033175
+2016-08-24 12:01:25,626 DEBUG: View 3 : 0.521327014218
+2016-08-24 12:01:25,899 DEBUG: Best view : MiRNA__
+2016-08-24 12:01:32,011 DEBUG: Start: Iteration 76
+2016-08-24 12:01:32,032 DEBUG: View 0 : 0.559241706161
+2016-08-24 12:01:32,042 DEBUG: View 1 : 0.549763033175
+2016-08-24 12:01:32,155 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:01:32,164 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:01:32,442 DEBUG: Best view : RANSeq_
+2016-08-24 12:01:38,648 DEBUG: Start: Iteration 77
+2016-08-24 12:01:38,669 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:01:38,679 DEBUG: View 1 : 0.620853080569
+2016-08-24 12:01:38,796 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:01:38,805 DEBUG: View 3 : 0.601895734597
+2016-08-24 12:01:39,085 DEBUG: Best view : Clinic_
+2016-08-24 12:01:45,370 DEBUG: Start: Iteration 78
+2016-08-24 12:01:45,392 DEBUG: View 0 : 0.42654028436
+2016-08-24 12:01:45,401 DEBUG: View 1 : 0.440758293839
+2016-08-24 12:01:45,518 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:01:45,528 DEBUG: View 3 : 0.715639810427
+2016-08-24 12:01:45,810 DEBUG: Best view : Clinic_
+2016-08-24 12:01:52,166 DEBUG: Start: Iteration 79
+2016-08-24 12:01:52,187 DEBUG: View 0 : 0.649289099526
+2016-08-24 12:01:52,196 DEBUG: View 1 : 0.63981042654
+2016-08-24 12:01:52,314 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:01:52,323 DEBUG: View 3 : 0.478672985782
+2016-08-24 12:01:52,609 DEBUG: Best view : Methyl_
+2016-08-24 12:01:59,070 DEBUG: Start: Iteration 80
+2016-08-24 12:01:59,092 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:01:59,101 DEBUG: View 1 : 0.469194312796
+2016-08-24 12:01:59,214 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:01:59,223 DEBUG: View 3 : 0.649289099526
+2016-08-24 12:01:59,513 DEBUG: Best view : Clinic_
+2016-08-24 12:02:06,043 DEBUG: Start: Iteration 81
+2016-08-24 12:02:06,064 DEBUG: View 0 : 0.654028436019
+2016-08-24 12:02:06,074 DEBUG: View 1 : 0.644549763033
+2016-08-24 12:02:06,186 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:02:06,195 DEBUG: View 3 : 0.63981042654
+2016-08-24 12:02:06,487 DEBUG: Best view : Clinic_
+2016-08-24 12:02:13,114 DEBUG: Start: Iteration 82
+2016-08-24 12:02:13,136 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:02:13,146 DEBUG: View 1 : 0.36018957346
+2016-08-24 12:02:13,274 DEBUG: View 2 : 0.526066350711
+2016-08-24 12:02:13,284 DEBUG: View 3 : 0.63981042654
+2016-08-24 12:02:13,581 DEBUG: Best view : Clinic_
+2016-08-24 12:02:20,360 DEBUG: Start: Iteration 83
+2016-08-24 12:02:20,381 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:02:20,391 DEBUG: View 1 : 0.654028436019
+2016-08-24 12:02:20,515 DEBUG: View 2 : 0.492890995261
+2016-08-24 12:02:20,524 DEBUG: View 3 : 0.563981042654
+2016-08-24 12:02:20,828 DEBUG: Best view : MiRNA__
+2016-08-24 12:02:27,746 DEBUG: Start: Iteration 84
+2016-08-24 12:02:27,767 DEBUG: View 0 : 0.57345971564
+2016-08-24 12:02:27,777 DEBUG: View 1 : 0.582938388626
+2016-08-24 12:02:27,933 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:02:27,942 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:02:28,242 DEBUG: Best view : RANSeq_
+2016-08-24 12:02:35,093 DEBUG: Start: Iteration 85
+2016-08-24 12:02:35,114 DEBUG: View 0 : 0.649289099526
+2016-08-24 12:02:35,124 DEBUG: View 1 : 0.63981042654
+2016-08-24 12:02:35,242 DEBUG: View 2 : 0.526066350711
+2016-08-24 12:02:35,251 DEBUG: View 3 : 0.431279620853
+2016-08-24 12:02:35,553 DEBUG: Best view : Methyl_
+2016-08-24 12:02:42,467 DEBUG: Start: Iteration 86
+2016-08-24 12:02:42,488 DEBUG: View 0 : 0.601895734597
+2016-08-24 12:02:42,498 DEBUG: View 1 : 0.431279620853
+2016-08-24 12:02:42,619 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:02:42,628 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:02:42,932 DEBUG: Best view : RANSeq_
+2016-08-24 12:02:49,946 DEBUG: Start: Iteration 87
+2016-08-24 12:02:49,965 DEBUG: View 0 : 0.369668246445
+2016-08-24 12:02:49,975 DEBUG: View 1 : 0.54028436019
+2016-08-24 12:02:50,088 DEBUG: View 2 : 0.63981042654
+2016-08-24 12:02:50,098 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:02:50,405 DEBUG: Best view : RANSeq_
+2016-08-24 12:02:57,532 DEBUG: Start: Iteration 88
+2016-08-24 12:02:57,553 DEBUG: View 0 : 0.436018957346
+2016-08-24 12:02:57,563 DEBUG: View 1 : 0.587677725118
+2016-08-24 12:02:57,676 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:02:57,685 DEBUG: View 3 : 0.644549763033
+2016-08-24 12:02:57,995 DEBUG: Best view : Clinic_
+2016-08-24 12:03:05,188 DEBUG: Start: Iteration 89
+2016-08-24 12:03:05,209 DEBUG: View 0 : 0.60663507109
+2016-08-24 12:03:05,219 DEBUG: View 1 : 0.663507109005
+2016-08-24 12:03:05,332 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:03:05,342 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:03:05,655 DEBUG: Best view : MiRNA__
+2016-08-24 12:03:12,949 DEBUG: Start: Iteration 90
+2016-08-24 12:03:12,969 DEBUG: View 0 : 0.597156398104
+2016-08-24 12:03:12,979 DEBUG: View 1 : 0.563981042654
+2016-08-24 12:03:13,100 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:03:13,109 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:03:13,425 DEBUG: Best view : Methyl_
+2016-08-24 12:03:20,775 DEBUG: Start: Iteration 91
+2016-08-24 12:03:20,796 DEBUG: View 0 : 0.497630331754
+2016-08-24 12:03:20,806 DEBUG: View 1 : 0.60663507109
+2016-08-24 12:03:20,925 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:03:20,934 DEBUG: View 3 : 0.582938388626
+2016-08-24 12:03:21,297 DEBUG: Best view : RANSeq_
+2016-08-24 12:03:28,741 DEBUG: Start: Iteration 92
+2016-08-24 12:03:28,762 DEBUG: View 0 : 0.54028436019
+2016-08-24 12:03:28,772 DEBUG: View 1 : 0.587677725118
+2016-08-24 12:03:28,877 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:03:28,886 DEBUG: View 3 : 0.549763033175
+2016-08-24 12:03:29,206 DEBUG: Best view : MiRNA__
+2016-08-24 12:03:36,720 DEBUG: Start: Iteration 93
+2016-08-24 12:03:36,741 DEBUG: View 0 : 0.473933649289
+2016-08-24 12:03:36,751 DEBUG: View 1 : 0.616113744076
+2016-08-24 12:03:36,873 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:03:36,882 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:03:37,206 DEBUG: Best view : Clinic_
+2016-08-24 12:03:44,800 DEBUG: Start: Iteration 94
+2016-08-24 12:03:44,822 DEBUG: View 0 : 0.469194312796
+2016-08-24 12:03:44,831 DEBUG: View 1 : 0.578199052133
+2016-08-24 12:03:44,953 DEBUG: View 2 : 0.616113744076
+2016-08-24 12:03:44,962 DEBUG: View 3 : 0.663507109005
+2016-08-24 12:03:45,290 DEBUG: Best view : Clinic_
+2016-08-24 12:03:52,966 DEBUG: Start: Iteration 95
+2016-08-24 12:03:52,988 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:03:52,997 DEBUG: View 1 : 0.687203791469
+2016-08-24 12:03:53,118 DEBUG: View 2 : 0.63981042654
+2016-08-24 12:03:53,128 DEBUG: View 3 : 0.587677725118
+2016-08-24 12:03:53,458 DEBUG: Best view : MiRNA__
+2016-08-24 12:04:01,211 DEBUG: Start: Iteration 96
+2016-08-24 12:04:01,232 DEBUG: View 0 : 0.469194312796
+2016-08-24 12:04:01,242 DEBUG: View 1 : 0.601895734597
+2016-08-24 12:04:01,350 DEBUG: View 2 : 0.611374407583
+2016-08-24 12:04:01,359 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:04:01,694 DEBUG: Best view : Clinic_
+2016-08-24 12:04:09,530 DEBUG: Start: Iteration 97
+2016-08-24 12:04:09,552 DEBUG: View 0 : 0.488151658768
+2016-08-24 12:04:09,563 DEBUG: View 1 : 0.436018957346
+2016-08-24 12:04:09,681 DEBUG: View 2 : 0.658767772512
+2016-08-24 12:04:09,690 DEBUG: View 3 : 0.630331753555
+2016-08-24 12:04:10,026 DEBUG: Best view : RANSeq_
+2016-08-24 12:04:17,961 DEBUG: Start: Iteration 98
+2016-08-24 12:04:17,982 DEBUG: View 0 : 0.464454976303
+2016-08-24 12:04:17,992 DEBUG: View 1 : 0.545023696682
+2016-08-24 12:04:18,109 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:04:18,118 DEBUG: View 3 : 0.526066350711
+2016-08-24 12:04:18,456 DEBUG: Best view : RANSeq_
+2016-08-24 12:04:26,502 DEBUG: Start: Iteration 99
+2016-08-24 12:04:26,523 DEBUG: View 0 : 0.563981042654
+2016-08-24 12:04:26,533 DEBUG: View 1 : 0.630331753555
+2016-08-24 12:04:26,641 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:04:26,651 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:04:26,992 DEBUG: Best view : RANSeq_
+2016-08-24 12:04:35,093 DEBUG: Start: Iteration 100
+2016-08-24 12:04:35,115 DEBUG: View 0 : 0.63981042654
+2016-08-24 12:04:35,125 DEBUG: View 1 : 0.450236966825
+2016-08-24 12:04:35,244 DEBUG: View 2 : 0.57345971564
+2016-08-24 12:04:35,254 DEBUG: View 3 : 0.554502369668
+2016-08-24 12:04:35,597 DEBUG: Best view : Methyl_
+2016-08-24 12:04:43,787 DEBUG: Start: Iteration 101
+2016-08-24 12:04:43,808 DEBUG: View 0 : 0.57345971564
+2016-08-24 12:04:43,818 DEBUG: View 1 : 0.587677725118
+2016-08-24 12:04:43,934 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:04:43,943 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:04:44,291 DEBUG: Best view : MiRNA__
+2016-08-24 12:04:52,538 DEBUG: Start: Iteration 102
+2016-08-24 12:04:52,559 DEBUG: View 0 : 0.507109004739
+2016-08-24 12:04:52,568 DEBUG: View 1 : 0.597156398104
+2016-08-24 12:04:52,681 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:04:52,690 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:04:53,040 DEBUG: Best view : MiRNA__
+2016-08-24 12:05:01,389 DEBUG: Start: Iteration 103
+2016-08-24 12:05:01,411 DEBUG: View 0 : 0.616113744076
+2016-08-24 12:05:01,421 DEBUG: View 1 : 0.545023696682
+2016-08-24 12:05:01,540 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:05:01,549 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:05:01,901 DEBUG: Best view : Clinic_
+2016-08-24 12:05:10,323 DEBUG: Start: Iteration 104
+2016-08-24 12:05:10,344 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:05:10,354 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:05:10,473 DEBUG: View 2 : 0.601895734597
+2016-08-24 12:05:10,482 DEBUG: View 3 : 0.535545023697
+2016-08-24 12:05:10,838 DEBUG: Best view : RANSeq_
+2016-08-24 12:05:19,346 DEBUG: Start: Iteration 105
+2016-08-24 12:05:19,367 DEBUG: View 0 : 0.601895734597
+2016-08-24 12:05:19,377 DEBUG: View 1 : 0.625592417062
+2016-08-24 12:05:19,491 DEBUG: View 2 : 0.526066350711
+2016-08-24 12:05:19,500 DEBUG: View 3 : 0.616113744076
+2016-08-24 12:05:19,859 DEBUG: Best view : Clinic_
+2016-08-24 12:05:28,447 DEBUG: Start: Iteration 106
+2016-08-24 12:05:28,468 DEBUG: View 0 : 0.601895734597
+2016-08-24 12:05:28,478 DEBUG: View 1 : 0.507109004739
+2016-08-24 12:05:28,592 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:05:28,601 DEBUG: View 3 : 0.54028436019
+2016-08-24 12:05:28,962 DEBUG: Best view : RANSeq_
+2016-08-24 12:05:37,647 DEBUG: Start: Iteration 107
+2016-08-24 12:05:37,668 DEBUG: View 0 : 0.601895734597
+2016-08-24 12:05:37,678 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:05:37,800 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:05:37,809 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:05:38,173 DEBUG: Best view : RANSeq_
+2016-08-24 12:05:46,950 DEBUG: Start: Iteration 108
+2016-08-24 12:05:46,971 DEBUG: View 0 : 0.630331753555
+2016-08-24 12:05:46,981 DEBUG: View 1 : 0.60663507109
+2016-08-24 12:05:47,093 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:05:47,102 DEBUG: View 3 : 0.715639810427
+2016-08-24 12:05:47,469 DEBUG: Best view : Clinic_
+2016-08-24 12:05:56,315 DEBUG: Start: Iteration 109
+2016-08-24 12:05:56,336 DEBUG: View 0 : 0.649289099526
+2016-08-24 12:05:56,345 DEBUG: View 1 : 0.582938388626
+2016-08-24 12:05:56,462 DEBUG: View 2 : 0.644549763033
+2016-08-24 12:05:56,471 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:05:56,844 DEBUG: Best view : RANSeq_
+2016-08-24 12:06:05,777 DEBUG: Start: Iteration 110
+2016-08-24 12:06:05,798 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:06:05,808 DEBUG: View 1 : 0.526066350711
+2016-08-24 12:06:05,930 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:06:05,939 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:06:06,312 DEBUG: Best view : Clinic_
+2016-08-24 12:06:15,323 DEBUG: Start: Iteration 111
+2016-08-24 12:06:15,344 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:06:15,354 DEBUG: View 1 : 0.545023696682
+2016-08-24 12:06:15,478 DEBUG: View 2 : 0.649289099526
+2016-08-24 12:06:15,488 DEBUG: View 3 : 0.60663507109
+2016-08-24 12:06:15,862 DEBUG: Best view : RANSeq_
+2016-08-24 12:06:24,977 DEBUG: Start: Iteration 112
+2016-08-24 12:06:24,998 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:06:25,008 DEBUG: View 1 : 0.563981042654
+2016-08-24 12:06:25,132 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:06:25,141 DEBUG: View 3 : 0.587677725118
+2016-08-24 12:06:25,522 DEBUG: Best view : Clinic_
+2016-08-24 12:06:34,714 DEBUG: Start: Iteration 113
+2016-08-24 12:06:34,735 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:06:34,744 DEBUG: View 1 : 0.507109004739
+2016-08-24 12:06:34,868 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:06:34,877 DEBUG: View 3 : 0.63981042654
+2016-08-24 12:06:35,257 DEBUG: Best view : Clinic_
+2016-08-24 12:06:44,518 DEBUG: Start: Iteration 114
+2016-08-24 12:06:44,539 DEBUG: View 0 : 0.445497630332
+2016-08-24 12:06:44,548 DEBUG: View 1 : 0.597156398104
+2016-08-24 12:06:44,669 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:06:44,679 DEBUG: View 3 : 0.611374407583
+2016-08-24 12:06:45,064 DEBUG: Best view : Clinic_
+2016-08-24 12:06:54,444 DEBUG: Start: Iteration 115
+2016-08-24 12:06:54,465 DEBUG: View 0 : 0.526066350711
+2016-08-24 12:06:54,475 DEBUG: View 1 : 0.63981042654
+2016-08-24 12:06:54,593 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:06:54,602 DEBUG: View 3 : 0.554502369668
+2016-08-24 12:06:54,988 DEBUG: Best view : MiRNA__
+2016-08-24 12:07:04,409 DEBUG: Start: Iteration 116
+2016-08-24 12:07:04,431 DEBUG: View 0 : 0.60663507109
+2016-08-24 12:07:04,441 DEBUG: View 1 : 0.734597156398
+2016-08-24 12:07:04,563 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:07:04,572 DEBUG: View 3 : 0.587677725118
+2016-08-24 12:07:04,967 DEBUG: Best view : MiRNA__
+2016-08-24 12:07:14,506 DEBUG: Start: Iteration 117
+2016-08-24 12:07:14,527 DEBUG: View 0 : 0.545023696682
+2016-08-24 12:07:14,537 DEBUG: View 1 : 0.611374407583
+2016-08-24 12:07:14,654 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:07:14,663 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:07:15,054 DEBUG: Best view : RANSeq_
+2016-08-24 12:07:24,664 DEBUG: Start: Iteration 118
+2016-08-24 12:07:24,686 DEBUG: View 0 : 0.649289099526
+2016-08-24 12:07:24,695 DEBUG: View 1 : 0.42654028436
+2016-08-24 12:07:24,813 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:07:24,823 DEBUG: View 3 : 0.620853080569
+2016-08-24 12:07:25,216 DEBUG: Best view : Methyl_
+2016-08-24 12:07:34,886 DEBUG: Start: Iteration 119
+2016-08-24 12:07:34,908 DEBUG: View 0 : 0.592417061611
+2016-08-24 12:07:34,918 DEBUG: View 1 : 0.649289099526
+2016-08-24 12:07:35,044 DEBUG: View 2 : 0.601895734597
+2016-08-24 12:07:35,053 DEBUG: View 3 : 0.601895734597
+2016-08-24 12:07:35,452 DEBUG: Best view : MiRNA__
+2016-08-24 12:07:45,211 DEBUG: Start: Iteration 120
+2016-08-24 12:07:45,232 DEBUG: View 0 : 0.545023696682
+2016-08-24 12:07:45,242 DEBUG: View 1 : 0.677725118483
+2016-08-24 12:07:45,365 DEBUG: View 2 : 0.511848341232
+2016-08-24 12:07:45,375 DEBUG: View 3 : 0.563981042654
+2016-08-24 12:07:45,780 DEBUG: Best view : MiRNA__
+2016-08-24 12:07:55,605 DEBUG: Start: Iteration 121
+2016-08-24 12:07:55,625 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:07:55,635 DEBUG: View 1 : 0.578199052133
+2016-08-24 12:07:55,752 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:07:55,761 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:07:56,167 DEBUG: Best view : Clinic_
+2016-08-24 12:08:06,056 DEBUG: Start: Iteration 122
+2016-08-24 12:08:06,077 DEBUG: View 0 : 0.587677725118
+2016-08-24 12:08:06,087 DEBUG: View 1 : 0.611374407583
+2016-08-24 12:08:06,205 DEBUG: View 2 : 0.511848341232
+2016-08-24 12:08:06,215 DEBUG: View 3 : 0.526066350711
+2016-08-24 12:08:06,620 DEBUG: Best view : MiRNA__
+2016-08-24 12:08:16,607 DEBUG: Start: Iteration 123
+2016-08-24 12:08:16,628 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:08:16,638 DEBUG: View 1 : 0.511848341232
+2016-08-24 12:08:16,760 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:08:16,769 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:08:17,180 DEBUG: Best view : Clinic_
+2016-08-24 12:08:27,249 DEBUG: Start: Iteration 124
+2016-08-24 12:08:27,270 DEBUG: View 0 : 0.545023696682
+2016-08-24 12:08:27,280 DEBUG: View 1 : 0.668246445498
+2016-08-24 12:08:27,393 DEBUG: View 2 : 0.57345971564
+2016-08-24 12:08:27,403 DEBUG: View 3 : 0.592417061611
+2016-08-24 12:08:27,816 DEBUG: Best view : MiRNA__
+2016-08-24 12:08:37,964 DEBUG: Start: Iteration 125
+2016-08-24 12:08:37,985 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:08:37,995 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:08:38,112 DEBUG: View 2 : 0.630331753555
+2016-08-24 12:08:38,121 DEBUG: View 3 : 0.654028436019
+2016-08-24 12:08:38,538 DEBUG: Best view : Clinic_
+2016-08-24 12:08:48,754 DEBUG: Start: Iteration 126
+2016-08-24 12:08:48,775 DEBUG: View 0 : 0.402843601896
+2016-08-24 12:08:48,785 DEBUG: View 1 : 0.644549763033
+2016-08-24 12:08:48,897 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:08:48,906 DEBUG: View 3 : 0.672985781991
+2016-08-24 12:08:49,326 DEBUG: Best view : Clinic_
+2016-08-24 12:08:59,605 DEBUG: Start: Iteration 127
+2016-08-24 12:08:59,626 DEBUG: View 0 : 0.663507109005
+2016-08-24 12:08:59,636 DEBUG: View 1 : 0.578199052133
+2016-08-24 12:08:59,753 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:08:59,763 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:09:00,192 DEBUG: Best view : Methyl_
+2016-08-24 12:09:10,552 DEBUG: Start: Iteration 128
+2016-08-24 12:09:10,573 DEBUG: View 0 : 0.672985781991
+2016-08-24 12:09:10,583 DEBUG: View 1 : 0.710900473934
+2016-08-24 12:09:10,705 DEBUG: View 2 : 0.502369668246
+2016-08-24 12:09:10,714 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:09:11,139 DEBUG: Best view : MiRNA__
+2016-08-24 12:09:21,574 DEBUG: Start: Iteration 129
+2016-08-24 12:09:21,595 DEBUG: View 0 : 0.663507109005
+2016-08-24 12:09:21,605 DEBUG: View 1 : 0.497630331754
+2016-08-24 12:09:21,726 DEBUG: View 2 : 0.57345971564
+2016-08-24 12:09:21,735 DEBUG: View 3 : 0.644549763033
+2016-08-24 12:09:22,164 DEBUG: Best view : Methyl_
+2016-08-24 12:09:32,723 DEBUG: Start: Iteration 130
+2016-08-24 12:09:32,744 DEBUG: View 0 : 0.611374407583
+2016-08-24 12:09:32,754 DEBUG: View 1 : 0.616113744076
+2016-08-24 12:09:32,869 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:09:32,878 DEBUG: View 3 : 0.644549763033
+2016-08-24 12:09:33,308 DEBUG: Best view : Clinic_
+2016-08-24 12:09:43,918 DEBUG: Start: Iteration 131
+2016-08-24 12:09:43,939 DEBUG: View 0 : 0.554502369668
+2016-08-24 12:09:43,949 DEBUG: View 1 : 0.554502369668
+2016-08-24 12:09:44,068 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:09:44,077 DEBUG: View 3 : 0.616113744076
+2016-08-24 12:09:44,512 DEBUG: Best view : Clinic_
+2016-08-24 12:09:55,225 DEBUG: Start: Iteration 132
+2016-08-24 12:09:55,246 DEBUG: View 0 : 0.563981042654
+2016-08-24 12:09:55,256 DEBUG: View 1 : 0.36018957346
+2016-08-24 12:09:55,373 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:09:55,383 DEBUG: View 3 : 0.625592417062
+2016-08-24 12:09:55,820 DEBUG: Best view : Clinic_
+2016-08-24 12:10:06,593 DEBUG: Start: Iteration 133
+2016-08-24 12:10:06,614 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:10:06,624 DEBUG: View 1 : 0.488151658768
+2016-08-24 12:10:06,736 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:10:06,746 DEBUG: View 3 : 0.710900473934
+2016-08-24 12:10:07,184 DEBUG: Best view : Clinic_
+2016-08-24 12:10:18,015 DEBUG: Start: Iteration 134
+2016-08-24 12:10:18,036 DEBUG: View 0 : 0.440758293839
+2016-08-24 12:10:18,046 DEBUG: View 1 : 0.677725118483
+2016-08-24 12:10:18,166 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:10:18,175 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:10:18,618 DEBUG: Best view : MiRNA__
+2016-08-24 12:10:29,538 DEBUG: Start: Iteration 135
+2016-08-24 12:10:29,560 DEBUG: View 0 : 0.45971563981
+2016-08-24 12:10:29,569 DEBUG: View 1 : 0.601895734597
+2016-08-24 12:10:29,693 DEBUG: View 2 : 0.502369668246
+2016-08-24 12:10:29,702 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:10:30,148 DEBUG: Best view : Clinic_
+2016-08-24 12:10:41,135 DEBUG: Start: Iteration 136
+2016-08-24 12:10:41,156 DEBUG: View 0 : 0.483412322275
+2016-08-24 12:10:41,165 DEBUG: View 1 : 0.710900473934
+2016-08-24 12:10:41,284 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:10:41,293 DEBUG: View 3 : 0.511848341232
+2016-08-24 12:10:41,741 DEBUG: Best view : MiRNA__
+2016-08-24 12:10:52,818 DEBUG: Start: Iteration 137
+2016-08-24 12:10:52,841 DEBUG: View 0 : 0.549763033175
+2016-08-24 12:10:52,850 DEBUG: View 1 : 0.554502369668
+2016-08-24 12:10:52,964 DEBUG: View 2 : 0.469194312796
+2016-08-24 12:10:52,974 DEBUG: View 3 : 0.516587677725
+2016-08-24 12:10:53,424 DEBUG: Best view : Methyl_
+2016-08-24 12:11:04,593 DEBUG: Start: Iteration 138
+2016-08-24 12:11:04,614 DEBUG: View 0 : 0.473933649289
+2016-08-24 12:11:04,624 DEBUG: View 1 : 0.701421800948
+2016-08-24 12:11:04,741 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:11:04,751 DEBUG: View 3 : 0.644549763033
+2016-08-24 12:11:05,209 DEBUG: Best view : MiRNA__
+2016-08-24 12:11:16,483 DEBUG: Start: Iteration 139
+2016-08-24 12:11:16,504 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:11:16,513 DEBUG: View 1 : 0.341232227488
+2016-08-24 12:11:16,631 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:11:16,640 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:11:17,099 DEBUG: Best view : Clinic_
+2016-08-24 12:11:28,407 DEBUG: Start: Iteration 140
+2016-08-24 12:11:28,428 DEBUG: View 0 : 0.658767772512
+2016-08-24 12:11:28,437 DEBUG: View 1 : 0.530805687204
+2016-08-24 12:11:28,550 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:11:28,559 DEBUG: View 3 : 0.511848341232
+2016-08-24 12:11:29,017 DEBUG: Best view : Methyl_
+2016-08-24 12:11:40,402 DEBUG: Start: Iteration 141
+2016-08-24 12:11:40,424 DEBUG: View 0 : 0.535545023697
+2016-08-24 12:11:40,434 DEBUG: View 1 : 0.526066350711
+2016-08-24 12:11:40,555 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:11:40,564 DEBUG: View 3 : 0.672985781991
+2016-08-24 12:11:41,028 DEBUG: Best view : Clinic_
+2016-08-24 12:11:52,497 DEBUG: Start: Iteration 142
+2016-08-24 12:11:52,519 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:11:52,528 DEBUG: View 1 : 0.60663507109
+2016-08-24 12:11:52,637 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:11:52,646 DEBUG: View 3 : 0.526066350711
+2016-08-24 12:11:53,112 DEBUG: Best view : MiRNA__
+2016-08-24 12:12:04,623 DEBUG: Start: Iteration 143
+2016-08-24 12:12:04,644 DEBUG: View 0 : 0.57345971564
+2016-08-24 12:12:04,654 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:12:04,776 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:12:04,786 DEBUG: View 3 : 0.616113744076
+2016-08-24 12:12:05,252 DEBUG: Best view : Clinic_
+2016-08-24 12:12:16,866 DEBUG: Start: Iteration 144
+2016-08-24 12:12:16,887 DEBUG: View 0 : 0.526066350711
+2016-08-24 12:12:16,897 DEBUG: View 1 : 0.388625592417
+2016-08-24 12:12:17,016 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:12:17,025 DEBUG: View 3 : 0.521327014218
+2016-08-24 12:12:17,502 DEBUG: Best view : RANSeq_
+2016-08-24 12:12:29,210 DEBUG: Start: Iteration 145
+2016-08-24 12:12:29,231 DEBUG: View 0 : 0.450236966825
+2016-08-24 12:12:29,241 DEBUG: View 1 : 0.620853080569
+2016-08-24 12:12:29,354 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:12:29,364 DEBUG: View 3 : 0.511848341232
+2016-08-24 12:12:29,840 DEBUG: Best view : MiRNA__
+2016-08-24 12:12:41,619 DEBUG: Start: Iteration 146
+2016-08-24 12:12:41,641 DEBUG: View 0 : 0.654028436019
+2016-08-24 12:12:41,650 DEBUG: View 1 : 0.511848341232
+2016-08-24 12:12:41,771 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:12:41,780 DEBUG: View 3 : 0.625592417062
+2016-08-24 12:12:42,255 DEBUG: Best view : Methyl_
+2016-08-24 12:12:54,122 DEBUG: Start: Iteration 147
+2016-08-24 12:12:54,143 DEBUG: View 0 : 0.729857819905
+2016-08-24 12:12:54,153 DEBUG: View 1 : 0.421800947867
+2016-08-24 12:12:54,271 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:12:54,281 DEBUG: View 3 : 0.592417061611
+2016-08-24 12:12:54,761 DEBUG: Best view : Methyl_
+2016-08-24 12:13:06,717 DEBUG: Start: Iteration 148
+2016-08-24 12:13:06,738 DEBUG: View 0 : 0.616113744076
+2016-08-24 12:13:06,748 DEBUG: View 1 : 0.696682464455
+2016-08-24 12:13:06,866 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:13:06,875 DEBUG: View 3 : 0.611374407583
+2016-08-24 12:13:07,360 DEBUG: Best view : MiRNA__
+2016-08-24 12:13:19,413 DEBUG: Start: Iteration 149
+2016-08-24 12:13:19,435 DEBUG: View 0 : 0.601895734597
+2016-08-24 12:13:19,444 DEBUG: View 1 : 0.672985781991
+2016-08-24 12:13:19,567 DEBUG: View 2 : 0.526066350711
+2016-08-24 12:13:19,576 DEBUG: View 3 : 0.554502369668
+2016-08-24 12:13:20,060 DEBUG: Best view : MiRNA__
+2016-08-24 12:13:32,162 DEBUG: Start: Iteration 150
+2016-08-24 12:13:32,183 DEBUG: View 0 : 0.42654028436
+2016-08-24 12:13:32,193 DEBUG: View 1 : 0.530805687204
+2016-08-24 12:13:32,314 DEBUG: View 2 : 0.620853080569
+2016-08-24 12:13:32,324 DEBUG: View 3 : 0.691943127962
+2016-08-24 12:13:32,822 DEBUG: Best view : Clinic_
+2016-08-24 12:13:45,034 DEBUG: Start: Iteration 151
+2016-08-24 12:13:45,056 DEBUG: View 0 : 0.57345971564
+2016-08-24 12:13:45,066 DEBUG: View 1 : 0.412322274882
+2016-08-24 12:13:45,192 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:13:45,201 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:13:45,693 DEBUG: Best view : Clinic_
+2016-08-24 12:13:57,957 DEBUG: Start: Iteration 152
+2016-08-24 12:13:57,979 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:13:57,988 DEBUG: View 1 : 0.549763033175
+2016-08-24 12:13:58,111 DEBUG: View 2 : 0.616113744076
+2016-08-24 12:13:58,120 DEBUG: View 3 : 0.592417061611
+2016-08-24 12:13:58,616 DEBUG: Best view : RANSeq_
+2016-08-24 12:14:10,970 DEBUG: Start: Iteration 153
+2016-08-24 12:14:10,991 DEBUG: View 0 : 0.616113744076
+2016-08-24 12:14:11,001 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:14:11,123 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:14:11,133 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:14:11,628 DEBUG: Best view : Methyl_
+2016-08-24 12:14:24,069 DEBUG: Start: Iteration 154
+2016-08-24 12:14:24,090 DEBUG: View 0 : 0.630331753555
+2016-08-24 12:14:24,100 DEBUG: View 1 : 0.682464454976
+2016-08-24 12:14:24,218 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:14:24,227 DEBUG: View 3 : 0.601895734597
+2016-08-24 12:14:24,731 DEBUG: Best view : MiRNA__
+2016-08-24 12:14:37,258 DEBUG: Start: Iteration 155
+2016-08-24 12:14:37,279 DEBUG: View 0 : 0.592417061611
+2016-08-24 12:14:37,288 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:14:37,409 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:14:37,418 DEBUG: View 3 : 0.672985781991
+2016-08-24 12:14:37,917 DEBUG: Best view : Clinic_
+2016-08-24 12:14:50,508 DEBUG: Start: Iteration 156
+2016-08-24 12:14:50,529 DEBUG: View 0 : 0.549763033175
+2016-08-24 12:14:50,539 DEBUG: View 1 : 0.625592417062
+2016-08-24 12:14:50,655 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:14:50,664 DEBUG: View 3 : 0.549763033175
+2016-08-24 12:14:51,169 DEBUG: Best view : MiRNA__
+2016-08-24 12:15:03,825 DEBUG: Start: Iteration 157
+2016-08-24 12:15:03,846 DEBUG: View 0 : 0.507109004739
+2016-08-24 12:15:03,855 DEBUG: View 1 : 0.592417061611
+2016-08-24 12:15:03,972 DEBUG: View 2 : 0.511848341232
+2016-08-24 12:15:03,981 DEBUG: View 3 : 0.535545023697
+2016-08-24 12:15:04,489 DEBUG: Best view : MiRNA__
+2016-08-24 12:15:17,235 DEBUG: Start: Iteration 158
+2016-08-24 12:15:17,257 DEBUG: View 0 : 0.526066350711
+2016-08-24 12:15:17,266 DEBUG: View 1 : 0.60663507109
+2016-08-24 12:15:17,384 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:15:17,394 DEBUG: View 3 : 0.54028436019
+2016-08-24 12:15:17,905 DEBUG: Best view : RANSeq_
+2016-08-24 12:15:30,740 DEBUG: Start: Iteration 159
+2016-08-24 12:15:30,761 DEBUG: View 0 : 0.658767772512
+2016-08-24 12:15:30,771 DEBUG: View 1 : 0.710900473934
+2016-08-24 12:15:30,890 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:15:30,899 DEBUG: View 3 : 0.663507109005
+2016-08-24 12:15:31,411 DEBUG: Best view : MiRNA__
+2016-08-24 12:15:44,313 DEBUG: Start: Iteration 160
+2016-08-24 12:15:44,334 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:15:44,344 DEBUG: View 1 : 0.597156398104
+2016-08-24 12:15:44,470 DEBUG: View 2 : 0.57345971564
+2016-08-24 12:15:44,479 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:15:44,994 DEBUG: Best view : Clinic_
+2016-08-24 12:15:58,000 DEBUG: Start: Iteration 161
+2016-08-24 12:15:58,021 DEBUG: View 0 : 0.815165876777
+2016-08-24 12:15:58,031 DEBUG: View 1 : 0.45971563981
+2016-08-24 12:15:58,144 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:15:58,153 DEBUG: View 3 : 0.582938388626
+2016-08-24 12:15:58,671 DEBUG: Best view : Methyl_
+2016-08-24 12:16:11,725 DEBUG: Start: Iteration 162
+2016-08-24 12:16:11,746 DEBUG: View 0 : 0.578199052133
+2016-08-24 12:16:11,756 DEBUG: View 1 : 0.549763033175
+2016-08-24 12:16:11,873 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:16:11,882 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:16:12,403 DEBUG: Best view : Methyl_
+2016-08-24 12:16:25,556 DEBUG: Start: Iteration 163
+2016-08-24 12:16:25,577 DEBUG: View 0 : 0.464454976303
+2016-08-24 12:16:25,586 DEBUG: View 1 : 0.549763033175
+2016-08-24 12:16:25,707 DEBUG: View 2 : 0.454976303318
+2016-08-24 12:16:25,716 DEBUG: View 3 : 0.563981042654
+2016-08-24 12:16:26,241 DEBUG: Best view : Clinic_
+2016-08-24 12:16:39,475 DEBUG: Start: Iteration 164
+2016-08-24 12:16:39,497 DEBUG: View 0 : 0.625592417062
+2016-08-24 12:16:39,506 DEBUG: View 1 : 0.545023696682
+2016-08-24 12:16:39,619 DEBUG: View 2 : 0.635071090047
+2016-08-24 12:16:39,628 DEBUG: View 3 : 0.521327014218
+2016-08-24 12:16:40,153 DEBUG: Best view : RANSeq_
+2016-08-24 12:16:53,496 DEBUG: Start: Iteration 165
+2016-08-24 12:16:53,517 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:16:53,527 DEBUG: View 1 : 0.635071090047
+2016-08-24 12:16:53,645 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:16:53,654 DEBUG: View 3 : 0.687203791469
+2016-08-24 12:16:54,187 DEBUG: Best view : Clinic_
+2016-08-24 12:17:07,598 DEBUG: Start: Iteration 166
+2016-08-24 12:17:07,619 DEBUG: View 0 : 0.436018957346
+2016-08-24 12:17:07,629 DEBUG: View 1 : 0.563981042654
+2016-08-24 12:17:07,735 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:17:07,744 DEBUG: View 3 : 0.478672985782
+2016-08-24 12:17:08,276 DEBUG: Best view : RANSeq_
+2016-08-24 12:17:21,774 DEBUG: Start: Iteration 167
+2016-08-24 12:17:21,796 DEBUG: View 0 : 0.473933649289
+2016-08-24 12:17:21,805 DEBUG: View 1 : 0.42654028436
+2016-08-24 12:17:21,922 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:17:21,931 DEBUG: View 3 : 0.672985781991
+2016-08-24 12:17:22,467 DEBUG: Best view : Clinic_
+2016-08-24 12:17:36,030 DEBUG: Start: Iteration 168
+2016-08-24 12:17:36,051 DEBUG: View 0 : 0.251184834123
+2016-08-24 12:17:36,061 DEBUG: View 1 : 0.597156398104
+2016-08-24 12:17:36,181 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:17:36,190 DEBUG: View 3 : 0.511848341232
+2016-08-24 12:17:36,730 DEBUG: Best view : MiRNA__
+2016-08-24 12:17:50,379 DEBUG: Start: Iteration 169
+2016-08-24 12:17:50,400 DEBUG: View 0 : 0.483412322275
+2016-08-24 12:17:50,410 DEBUG: View 1 : 0.45971563981
+2016-08-24 12:17:50,528 DEBUG: View 2 : 0.616113744076
+2016-08-24 12:17:50,537 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:17:51,078 DEBUG: Best view : RANSeq_
+2016-08-24 12:18:04,862 DEBUG: Start: Iteration 170
+2016-08-24 12:18:04,884 DEBUG: View 0 : 0.559241706161
+2016-08-24 12:18:04,894 DEBUG: View 1 : 0.649289099526
+2016-08-24 12:18:05,012 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:18:05,021 DEBUG: View 3 : 0.630331753555
+2016-08-24 12:18:05,570 DEBUG: Best view : MiRNA__
+2016-08-24 12:18:19,413 DEBUG: Start: Iteration 171
+2016-08-24 12:18:19,434 DEBUG: View 0 : 0.36018957346
+2016-08-24 12:18:19,444 DEBUG: View 1 : 0.511848341232
+2016-08-24 12:18:19,561 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:18:19,570 DEBUG: View 3 : 0.601895734597
+2016-08-24 12:18:20,121 DEBUG: Best view : Clinic_
+2016-08-24 12:18:34,055 DEBUG: Start: Iteration 172
+2016-08-24 12:18:34,076 DEBUG: View 0 : 0.672985781991
+2016-08-24 12:18:34,085 DEBUG: View 1 : 0.497630331754
+2016-08-24 12:18:34,207 DEBUG: View 2 : 0.635071090047
+2016-08-24 12:18:34,216 DEBUG: View 3 : 0.658767772512
+2016-08-24 12:18:34,767 DEBUG: Best view : Clinic_
+2016-08-24 12:18:48,760 DEBUG: Start: Iteration 173
+2016-08-24 12:18:48,781 DEBUG: View 0 : 0.54028436019
+2016-08-24 12:18:48,790 DEBUG: View 1 : 0.473933649289
+2016-08-24 12:18:48,903 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:18:48,912 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:18:49,465 DEBUG: Best view : Clinic_
+2016-08-24 12:19:03,546 DEBUG: Start: Iteration 174
+2016-08-24 12:19:03,567 DEBUG: View 0 : 0.436018957346
+2016-08-24 12:19:03,577 DEBUG: View 1 : 0.488151658768
+2016-08-24 12:19:03,694 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:19:03,704 DEBUG: View 3 : 0.616113744076
+2016-08-24 12:19:04,260 DEBUG: Best view : Clinic_
+2016-08-24 12:19:18,387 DEBUG: Start: Iteration 175
+2016-08-24 12:19:18,408 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:19:18,417 DEBUG: View 1 : 0.578199052133
+2016-08-24 12:19:18,530 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:19:18,539 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:19:19,102 DEBUG: Best view : Methyl_
+2016-08-24 12:19:33,321 DEBUG: Start: Iteration 176
+2016-08-24 12:19:33,343 DEBUG: View 0 : 0.611374407583
+2016-08-24 12:19:33,353 DEBUG: View 1 : 0.355450236967
+2016-08-24 12:19:33,475 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:19:33,484 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:19:34,046 DEBUG: Best view : Clinic_
+2016-08-24 12:19:48,336 DEBUG: Start: Iteration 177
+2016-08-24 12:19:48,357 DEBUG: View 0 : 0.559241706161
+2016-08-24 12:19:48,367 DEBUG: View 1 : 0.516587677725
+2016-08-24 12:19:48,483 DEBUG: View 2 : 0.616113744076
+2016-08-24 12:19:48,492 DEBUG: View 3 : 0.691943127962
+2016-08-24 12:19:49,059 DEBUG: Best view : Clinic_
+2016-08-24 12:20:03,424 DEBUG: Start: Iteration 178
+2016-08-24 12:20:03,446 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:20:03,455 DEBUG: View 1 : 0.668246445498
+2016-08-24 12:20:03,569 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:20:03,578 DEBUG: View 3 : 0.549763033175
+2016-08-24 12:20:04,145 DEBUG: Best view : MiRNA__
+2016-08-24 12:20:18,599 DEBUG: Start: Iteration 179
+2016-08-24 12:20:18,620 DEBUG: View 0 : 0.578199052133
+2016-08-24 12:20:18,629 DEBUG: View 1 : 0.625592417062
+2016-08-24 12:20:18,751 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:20:18,760 DEBUG: View 3 : 0.710900473934
+2016-08-24 12:20:19,336 DEBUG: Best view : Clinic_
+2016-08-24 12:20:33,854 DEBUG: Start: Iteration 180
+2016-08-24 12:20:33,875 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:20:33,884 DEBUG: View 1 : 0.611374407583
+2016-08-24 12:20:34,004 DEBUG: View 2 : 0.507109004739
+2016-08-24 12:20:34,013 DEBUG: View 3 : 0.663507109005
+2016-08-24 12:20:34,586 DEBUG: Best view : Clinic_
+2016-08-24 12:20:49,180 DEBUG: Start: Iteration 181
+2016-08-24 12:20:49,201 DEBUG: View 0 : 0.45971563981
+2016-08-24 12:20:49,211 DEBUG: View 1 : 0.383886255924
+2016-08-24 12:20:49,328 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:20:49,338 DEBUG: View 3 : 0.710900473934
+2016-08-24 12:20:49,925 DEBUG: Best view : Clinic_
+2016-08-24 12:21:04,606 DEBUG: Start: Iteration 182
+2016-08-24 12:21:04,628 DEBUG: View 0 : 0.587677725118
+2016-08-24 12:21:04,637 DEBUG: View 1 : 0.582938388626
+2016-08-24 12:21:04,757 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:21:04,766 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:21:05,345 DEBUG: Best view : Clinic_
+2016-08-24 12:21:20,109 DEBUG: Start: Iteration 183
+2016-08-24 12:21:20,131 DEBUG: View 0 : 0.696682464455
+2016-08-24 12:21:20,140 DEBUG: View 1 : 0.625592417062
+2016-08-24 12:21:20,257 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:21:20,266 DEBUG: View 3 : 0.587677725118
+2016-08-24 12:21:20,850 DEBUG: Best view : Methyl_
+2016-08-24 12:21:35,677 DEBUG: Start: Iteration 184
+2016-08-24 12:21:35,698 DEBUG: View 0 : 0.483412322275
+2016-08-24 12:21:35,708 DEBUG: View 1 : 0.620853080569
+2016-08-24 12:21:35,825 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:21:35,835 DEBUG: View 3 : 0.54028436019
+2016-08-24 12:21:36,423 DEBUG: Best view : MiRNA__
+2016-08-24 12:21:51,330 DEBUG: Start: Iteration 185
+2016-08-24 12:21:51,351 DEBUG: View 0 : 0.635071090047
+2016-08-24 12:21:51,361 DEBUG: View 1 : 0.706161137441
+2016-08-24 12:21:51,480 DEBUG: View 2 : 0.616113744076
+2016-08-24 12:21:51,490 DEBUG: View 3 : 0.54028436019
+2016-08-24 12:21:52,074 DEBUG: Best view : MiRNA__
+2016-08-24 12:22:07,069 DEBUG: Start: Iteration 186
+2016-08-24 12:22:07,090 DEBUG: View 0 : 0.545023696682
+2016-08-24 12:22:07,100 DEBUG: View 1 : 0.45971563981
+2016-08-24 12:22:07,220 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:22:07,229 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:22:07,825 DEBUG: Best view : RANSeq_
+2016-08-24 12:22:22,929 DEBUG: Start: Iteration 187
+2016-08-24 12:22:22,950 DEBUG: View 0 : 0.672985781991
+2016-08-24 12:22:22,959 DEBUG: View 1 : 0.725118483412
+2016-08-24 12:22:23,078 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:22:23,088 DEBUG: View 3 : 0.620853080569
+2016-08-24 12:22:23,683 DEBUG: Best view : MiRNA__
+2016-08-24 12:22:38,861 DEBUG: Start: Iteration 188
+2016-08-24 12:22:38,882 DEBUG: View 0 : 0.625592417062
+2016-08-24 12:22:38,892 DEBUG: View 1 : 0.549763033175
+2016-08-24 12:22:39,013 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:22:39,022 DEBUG: View 3 : 0.677725118483
+2016-08-24 12:22:39,617 DEBUG: Best view : Clinic_
+2016-08-24 12:22:54,875 DEBUG: Start: Iteration 189
+2016-08-24 12:22:54,896 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:22:54,906 DEBUG: View 1 : 0.412322274882
+2016-08-24 12:22:55,034 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:22:55,043 DEBUG: View 3 : 0.582938388626
+2016-08-24 12:22:55,648 DEBUG: Best view : RANSeq_
+2016-08-24 12:23:10,946 DEBUG: Start: Iteration 190
+2016-08-24 12:23:10,967 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:23:10,977 DEBUG: View 1 : 0.440758293839
+2016-08-24 12:23:11,109 DEBUG: View 2 : 0.473933649289
+2016-08-24 12:23:11,118 DEBUG: View 3 : 0.625592417062
+2016-08-24 12:23:11,721 DEBUG: Best view : Clinic_
+2016-08-24 12:23:27,156 DEBUG: Start: Iteration 191
+2016-08-24 12:23:27,177 DEBUG: View 0 : 0.497630331754
+2016-08-24 12:23:27,187 DEBUG: View 1 : 0.644549763033
+2016-08-24 12:23:27,310 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:23:27,320 DEBUG: View 3 : 0.63981042654
+2016-08-24 12:23:27,920 DEBUG: Best view : Clinic_
+2016-08-24 12:23:43,375 DEBUG: Start: Iteration 192
+2016-08-24 12:23:43,396 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:23:43,406 DEBUG: View 1 : 0.620853080569
+2016-08-24 12:23:43,540 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:23:43,551 DEBUG: View 3 : 0.587677725118
+2016-08-24 12:23:44,160 DEBUG: Best view : Methyl_
+2016-08-24 12:23:59,708 DEBUG: Start: Iteration 193
+2016-08-24 12:23:59,730 DEBUG: View 0 : 0.516587677725
+2016-08-24 12:23:59,739 DEBUG: View 1 : 0.417061611374
+2016-08-24 12:23:59,880 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:23:59,892 DEBUG: View 3 : 0.535545023697
+2016-08-24 12:24:00,504 DEBUG: Best view : Clinic_
+2016-08-24 12:24:16,134 DEBUG: Start: Iteration 194
+2016-08-24 12:24:16,155 DEBUG: View 0 : 0.39336492891
+2016-08-24 12:24:16,165 DEBUG: View 1 : 0.478672985782
+2016-08-24 12:24:16,296 DEBUG: View 2 : 0.511848341232
+2016-08-24 12:24:16,308 DEBUG: View 3 : 0.658767772512
+2016-08-24 12:24:16,929 DEBUG: Best view : Clinic_
+2016-08-24 12:24:32,642 DEBUG: Start: Iteration 195
+2016-08-24 12:24:32,663 DEBUG: View 0 : 0.587677725118
+2016-08-24 12:24:32,673 DEBUG: View 1 : 0.587677725118
+2016-08-24 12:24:32,808 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:24:32,819 DEBUG: View 3 : 0.545023696682
+2016-08-24 12:24:33,438 DEBUG: Best view : RANSeq_
+2016-08-24 12:24:49,256 DEBUG: Start: Iteration 196
+2016-08-24 12:24:49,277 DEBUG: View 0 : 0.592417061611
+2016-08-24 12:24:49,287 DEBUG: View 1 : 0.469194312796
+2016-08-24 12:24:49,418 DEBUG: View 2 : 0.649289099526
+2016-08-24 12:24:49,430 DEBUG: View 3 : 0.492890995261
+2016-08-24 12:24:50,049 DEBUG: Best view : RANSeq_
+2016-08-24 12:25:05,942 DEBUG: Start: Iteration 197
+2016-08-24 12:25:05,961 DEBUG: View 0 : 0.497630331754
+2016-08-24 12:25:05,971 DEBUG: View 1 : 0.549763033175
+2016-08-24 12:25:06,106 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:25:06,118 DEBUG: View 3 : 0.554502369668
+2016-08-24 12:25:06,739 DEBUG: Best view : RANSeq_
+2016-08-24 12:25:22,740 DEBUG: Start: Iteration 198
+2016-08-24 12:25:22,761 DEBUG: View 0 : 0.535545023697
+2016-08-24 12:25:22,771 DEBUG: View 1 : 0.672985781991
+2016-08-24 12:25:22,906 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:25:22,918 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:25:23,544 DEBUG: Best view : MiRNA__
+2016-08-24 12:25:39,634 DEBUG: Start: Iteration 199
+2016-08-24 12:25:39,655 DEBUG: View 0 : 0.597156398104
+2016-08-24 12:25:39,665 DEBUG: View 1 : 0.691943127962
+2016-08-24 12:25:39,791 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:25:39,803 DEBUG: View 3 : 0.625592417062
+2016-08-24 12:25:40,445 DEBUG: Best view : MiRNA__
+2016-08-24 12:25:56,609 DEBUG: Start: Iteration 200
+2016-08-24 12:25:56,631 DEBUG: View 0 : 0.644549763033
+2016-08-24 12:25:56,640 DEBUG: View 1 : 0.54028436019
+2016-08-24 12:25:56,772 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:25:56,783 DEBUG: View 3 : 0.701421800948
+2016-08-24 12:25:57,413 DEBUG: Best view : Clinic_
+2016-08-24 12:26:13,644 DEBUG: Start: Iteration 201
+2016-08-24 12:26:13,665 DEBUG: View 0 : 0.440758293839
+2016-08-24 12:26:13,675 DEBUG: View 1 : 0.635071090047
+2016-08-24 12:26:13,806 DEBUG: View 2 : 0.620853080569
+2016-08-24 12:26:13,818 DEBUG: View 3 : 0.511848341232
+2016-08-24 12:26:14,451 DEBUG: Best view : RANSeq_
+2016-08-24 12:26:30,791 DEBUG: Start: Iteration 202
+2016-08-24 12:26:30,813 DEBUG: View 0 : 0.54028436019
+2016-08-24 12:26:30,822 DEBUG: View 1 : 0.398104265403
+2016-08-24 12:26:30,963 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:26:30,974 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:26:31,610 DEBUG: Best view : RANSeq_
+2016-08-24 12:26:48,031 DEBUG: Start: Iteration 203
+2016-08-24 12:26:48,052 DEBUG: View 0 : 0.630331753555
+2016-08-24 12:26:48,062 DEBUG: View 1 : 0.54028436019
+2016-08-24 12:26:48,172 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:26:48,184 DEBUG: View 3 : 0.663507109005
+2016-08-24 12:26:48,822 DEBUG: Best view : Clinic_
+2016-08-24 12:27:05,312 DEBUG: Start: Iteration 204
+2016-08-24 12:27:05,334 DEBUG: View 0 : 0.478672985782
+2016-08-24 12:27:05,344 DEBUG: View 1 : 0.473933649289
+2016-08-24 12:27:05,472 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:27:05,484 DEBUG: View 3 : 0.672985781991
+2016-08-24 12:27:06,126 DEBUG: Best view : Clinic_
+2016-08-24 12:27:22,687 DEBUG: Start: Iteration 205
+2016-08-24 12:27:22,709 DEBUG: View 0 : 0.625592417062
+2016-08-24 12:27:22,718 DEBUG: View 1 : 0.568720379147
+2016-08-24 12:27:22,856 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:27:22,868 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:27:23,510 DEBUG: Best view : Clinic_
+2016-08-24 12:27:40,173 DEBUG: Start: Iteration 206
+2016-08-24 12:27:40,194 DEBUG: View 0 : 0.483412322275
+2016-08-24 12:27:40,204 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:27:40,338 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:27:40,349 DEBUG: View 3 : 0.601895734597
+2016-08-24 12:27:41,001 DEBUG: Best view : RANSeq_
+2016-08-24 12:27:57,762 DEBUG: Start: Iteration 207
+2016-08-24 12:27:57,783 DEBUG: View 0 : 0.601895734597
+2016-08-24 12:27:57,793 DEBUG: View 1 : 0.663507109005
+2016-08-24 12:27:57,928 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:27:57,939 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:27:58,591 DEBUG: Best view : MiRNA__
+2016-08-24 12:28:15,463 DEBUG: Start: Iteration 208
+2016-08-24 12:28:15,484 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:28:15,494 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:28:15,627 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:28:15,638 DEBUG: View 3 : 0.611374407583
+2016-08-24 12:28:16,292 DEBUG: Best view : Clinic_
+2016-08-24 12:28:33,226 DEBUG: Start: Iteration 209
+2016-08-24 12:28:33,247 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:28:33,257 DEBUG: View 1 : 0.677725118483
+2016-08-24 12:28:33,393 DEBUG: View 2 : 0.601895734597
+2016-08-24 12:28:33,404 DEBUG: View 3 : 0.582938388626
+2016-08-24 12:28:34,062 DEBUG: Best view : MiRNA__
+2016-08-24 12:28:51,028 DEBUG: Start: Iteration 210
+2016-08-24 12:28:51,049 DEBUG: View 0 : 0.535545023697
+2016-08-24 12:28:51,059 DEBUG: View 1 : 0.578199052133
+2016-08-24 12:28:51,182 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:28:51,194 DEBUG: View 3 : 0.616113744076
+2016-08-24 12:28:51,859 DEBUG: Best view : Clinic_
+2016-08-24 12:29:08,915 DEBUG: Start: Iteration 211
+2016-08-24 12:29:08,936 DEBUG: View 0 : 0.582938388626
+2016-08-24 12:29:08,945 DEBUG: View 1 : 0.654028436019
+2016-08-24 12:29:09,080 DEBUG: View 2 : 0.526066350711
+2016-08-24 12:29:09,091 DEBUG: View 3 : 0.535545023697
+2016-08-24 12:29:09,755 DEBUG: Best view : MiRNA__
+2016-08-24 12:29:26,868 DEBUG: Start: Iteration 212
+2016-08-24 12:29:26,889 DEBUG: View 0 : 0.483412322275
+2016-08-24 12:29:26,899 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:29:27,034 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:29:27,046 DEBUG: View 3 : 0.668246445498
+2016-08-24 12:29:27,711 DEBUG: Best view : Clinic_
+2016-08-24 12:29:44,959 DEBUG: Start: Iteration 213
+2016-08-24 12:29:44,980 DEBUG: View 0 : 0.464454976303
+2016-08-24 12:29:44,990 DEBUG: View 1 : 0.507109004739
+2016-08-24 12:29:45,125 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:29:45,136 DEBUG: View 3 : 0.60663507109
+2016-08-24 12:29:45,810 DEBUG: Best view : Clinic_
+2016-08-24 12:30:03,096 DEBUG: Start: Iteration 214
+2016-08-24 12:30:03,118 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:30:03,127 DEBUG: View 1 : 0.549763033175
+2016-08-24 12:30:03,252 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:30:03,263 DEBUG: View 3 : 0.502369668246
+2016-08-24 12:30:03,934 DEBUG: Best view : RANSeq_
+2016-08-24 12:30:21,334 DEBUG: Start: Iteration 215
+2016-08-24 12:30:21,355 DEBUG: View 0 : 0.492890995261
+2016-08-24 12:30:21,365 DEBUG: View 1 : 0.687203791469
+2016-08-24 12:30:21,499 DEBUG: View 2 : 0.488151658768
+2016-08-24 12:30:21,508 DEBUG: View 3 : 0.483412322275
+2016-08-24 12:30:22,180 DEBUG: Best view : MiRNA__
+2016-08-24 12:30:39,659 DEBUG: Start: Iteration 216
+2016-08-24 12:30:39,680 DEBUG: View 0 : 0.507109004739
+2016-08-24 12:30:39,690 DEBUG: View 1 : 0.720379146919
+2016-08-24 12:30:39,811 DEBUG: View 2 : 0.492890995261
+2016-08-24 12:30:39,820 DEBUG: View 3 : 0.691943127962
+2016-08-24 12:30:40,498 DEBUG: Best view : MiRNA__
+2016-08-24 12:30:58,038 DEBUG: Start: Iteration 217
+2016-08-24 12:30:58,059 DEBUG: View 0 : 0.668246445498
+2016-08-24 12:30:58,069 DEBUG: View 1 : 0.682464454976
+2016-08-24 12:30:58,190 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:30:58,200 DEBUG: View 3 : 0.526066350711
+2016-08-24 12:30:58,880 DEBUG: Best view : MiRNA__
+2016-08-24 12:31:16,516 DEBUG: Start: Iteration 218
+2016-08-24 12:31:16,537 DEBUG: View 0 : 0.535545023697
+2016-08-24 12:31:16,547 DEBUG: View 1 : 0.63981042654
+2016-08-24 12:31:16,670 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:31:16,679 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:31:17,364 DEBUG: Best view : Clinic_
+2016-08-24 12:31:35,062 DEBUG: Start: Iteration 219
+2016-08-24 12:31:35,083 DEBUG: View 0 : 0.436018957346
+2016-08-24 12:31:35,092 DEBUG: View 1 : 0.502369668246
+2016-08-24 12:31:35,218 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:31:35,227 DEBUG: View 3 : 0.649289099526
+2016-08-24 12:31:35,914 DEBUG: Best view : Clinic_
+2016-08-24 12:31:53,669 DEBUG: Start: Iteration 220
+2016-08-24 12:31:53,690 DEBUG: View 0 : 0.706161137441
+2016-08-24 12:31:53,700 DEBUG: View 1 : 0.620853080569
+2016-08-24 12:31:53,823 DEBUG: View 2 : 0.54028436019
+2016-08-24 12:31:53,832 DEBUG: View 3 : 0.592417061611
+2016-08-24 12:31:54,527 DEBUG: Best view : Methyl_
+2016-08-24 12:32:12,385 DEBUG: Start: Iteration 221
+2016-08-24 12:32:12,406 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:32:12,416 DEBUG: View 1 : 0.492890995261
+2016-08-24 12:32:12,539 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:32:12,548 DEBUG: View 3 : 0.554502369668
+2016-08-24 12:32:13,236 DEBUG: Best view : RANSeq_
+2016-08-24 12:32:31,134 DEBUG: Start: Iteration 222
+2016-08-24 12:32:31,155 DEBUG: View 0 : 0.587677725118
+2016-08-24 12:32:31,165 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:32:31,296 DEBUG: View 2 : 0.549763033175
+2016-08-24 12:32:31,305 DEBUG: View 3 : 0.54028436019
+2016-08-24 12:32:32,001 DEBUG: Best view : Methyl_
+2016-08-24 12:32:49,999 DEBUG: Start: Iteration 223
+2016-08-24 12:32:50,020 DEBUG: View 0 : 0.497630331754
+2016-08-24 12:32:50,029 DEBUG: View 1 : 0.81990521327
+2016-08-24 12:32:50,164 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:32:50,174 DEBUG: View 3 : 0.60663507109
+2016-08-24 12:32:50,871 DEBUG: Best view : MiRNA__
+2016-08-24 12:33:08,927 DEBUG: Start: Iteration 224
+2016-08-24 12:33:08,948 DEBUG: View 0 : 0.464454976303
+2016-08-24 12:33:08,957 DEBUG: View 1 : 0.293838862559
+2016-08-24 12:33:09,076 DEBUG: View 2 : 0.644549763033
+2016-08-24 12:33:09,085 DEBUG: View 3 : 0.630331753555
+2016-08-24 12:33:09,787 DEBUG: Best view : RANSeq_
+2016-08-24 12:33:27,976 DEBUG: Start: Iteration 225
+2016-08-24 12:33:27,997 DEBUG: View 0 : 0.388625592417
+2016-08-24 12:33:28,007 DEBUG: View 1 : 0.805687203791
+2016-08-24 12:33:28,130 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:33:28,140 DEBUG: View 3 : 0.611374407583
+2016-08-24 12:33:28,840 DEBUG: Best view : MiRNA__
+2016-08-24 12:33:47,106 DEBUG: Start: Iteration 226
+2016-08-24 12:33:47,128 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:33:47,138 DEBUG: View 1 : 0.677725118483
+2016-08-24 12:33:47,268 DEBUG: View 2 : 0.516587677725
+2016-08-24 12:33:47,278 DEBUG: View 3 : 0.649289099526
+2016-08-24 12:33:47,984 DEBUG: Best view : Clinic_
+2016-08-24 12:34:06,263 DEBUG: Start: Iteration 227
+2016-08-24 12:34:06,284 DEBUG: View 0 : 0.57345971564
+2016-08-24 12:34:06,294 DEBUG: View 1 : 0.620853080569
+2016-08-24 12:34:06,422 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:34:06,432 DEBUG: View 3 : 0.60663507109
+2016-08-24 12:34:07,137 DEBUG: Best view : Clinic_
+2016-08-24 12:34:25,806 DEBUG: Start: Iteration 228
+2016-08-24 12:34:25,830 DEBUG: View 0 : 0.563981042654
+2016-08-24 12:34:25,843 DEBUG: View 1 : 0.526066350711
+2016-08-24 12:34:26,007 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:34:26,017 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:34:26,767 DEBUG: Best view : RANSeq_
+2016-08-24 12:34:46,243 DEBUG: Start: Iteration 229
+2016-08-24 12:34:46,265 DEBUG: View 0 : 0.57345971564
+2016-08-24 12:34:46,276 DEBUG: View 1 : 0.654028436019
+2016-08-24 12:34:46,453 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:34:46,463 DEBUG: View 3 : 0.592417061611
+2016-08-24 12:34:47,215 DEBUG: Best view : MiRNA__
+2016-08-24 12:35:05,992 DEBUG: Start: Iteration 230
+2016-08-24 12:35:06,013 DEBUG: View 0 : 0.616113744076
+2016-08-24 12:35:06,023 DEBUG: View 1 : 0.431279620853
+2016-08-24 12:35:06,139 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:35:06,150 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:35:06,863 DEBUG: Best view : Clinic_
+2016-08-24 12:35:25,551 DEBUG: Start: Iteration 231
+2016-08-24 12:35:25,573 DEBUG: View 0 : 0.450236966825
+2016-08-24 12:35:25,583 DEBUG: View 1 : 0.635071090047
+2016-08-24 12:35:25,703 DEBUG: View 2 : 0.616113744076
+2016-08-24 12:35:25,713 DEBUG: View 3 : 0.545023696682
+2016-08-24 12:35:26,428 DEBUG: Best view : RANSeq_
+2016-08-24 12:35:45,202 DEBUG: Start: Iteration 232
+2016-08-24 12:35:45,223 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:35:45,233 DEBUG: View 1 : 0.469194312796
+2016-08-24 12:35:45,356 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:35:45,366 DEBUG: View 3 : 0.478672985782
+2016-08-24 12:35:46,085 DEBUG: Best view : Methyl_
+2016-08-24 12:36:04,939 DEBUG: Start: Iteration 233
+2016-08-24 12:36:04,960 DEBUG: View 0 : 0.554502369668
+2016-08-24 12:36:04,970 DEBUG: View 1 : 0.568720379147
+2016-08-24 12:36:05,097 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:36:05,106 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:36:05,830 DEBUG: Best view : Clinic_
+2016-08-24 12:36:24,753 DEBUG: Start: Iteration 234
+2016-08-24 12:36:24,773 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:36:24,783 DEBUG: View 1 : 0.511848341232
+2016-08-24 12:36:24,899 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:36:24,908 DEBUG: View 3 : 0.563981042654
+2016-08-24 12:36:25,636 DEBUG: Best view : Clinic_
+2016-08-24 12:36:44,616 DEBUG: Start: Iteration 235
+2016-08-24 12:36:44,637 DEBUG: View 0 : 0.469194312796
+2016-08-24 12:36:44,647 DEBUG: View 1 : 0.42654028436
+2016-08-24 12:36:44,761 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:36:44,770 DEBUG: View 3 : 0.701421800948
+2016-08-24 12:36:45,502 DEBUG: Best view : Clinic_
+2016-08-24 12:37:04,540 DEBUG: Start: Iteration 236
+2016-08-24 12:37:04,562 DEBUG: View 0 : 0.445497630332
+2016-08-24 12:37:04,573 DEBUG: View 1 : 0.478672985782
+2016-08-24 12:37:04,691 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:37:04,700 DEBUG: View 3 : 0.701421800948
+2016-08-24 12:37:05,432 DEBUG: Best view : Clinic_
+2016-08-24 12:37:24,538 DEBUG: Start: Iteration 237
+2016-08-24 12:37:24,559 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:37:24,569 DEBUG: View 1 : 0.582938388626
+2016-08-24 12:37:24,691 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:37:24,700 DEBUG: View 3 : 0.625592417062
+2016-08-24 12:37:25,438 DEBUG: Best view : Clinic_
+2016-08-24 12:37:44,807 DEBUG: Start: Iteration 238
+2016-08-24 12:37:44,828 DEBUG: View 0 : 0.625592417062
+2016-08-24 12:37:44,838 DEBUG: View 1 : 0.597156398104
+2016-08-24 12:37:44,955 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:37:44,964 DEBUG: View 3 : 0.559241706161
+2016-08-24 12:37:45,704 DEBUG: Best view : Methyl_
+2016-08-24 12:38:05,054 DEBUG: Start: Iteration 239
+2016-08-24 12:38:05,076 DEBUG: View 0 : 0.725118483412
+2016-08-24 12:38:05,085 DEBUG: View 1 : 0.682464454976
+2016-08-24 12:38:05,204 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:38:05,213 DEBUG: View 3 : 0.516587677725
+2016-08-24 12:38:05,956 DEBUG: Best view : Methyl_
+2016-08-24 12:38:25,314 DEBUG: Start: Iteration 240
+2016-08-24 12:38:25,335 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:38:25,345 DEBUG: View 1 : 0.635071090047
+2016-08-24 12:38:25,474 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:38:25,483 DEBUG: View 3 : 0.563981042654
+2016-08-24 12:38:26,227 DEBUG: Best view : MiRNA__
+2016-08-24 12:38:45,701 DEBUG: Start: Iteration 241
+2016-08-24 12:38:45,723 DEBUG: View 0 : 0.545023696682
+2016-08-24 12:38:45,733 DEBUG: View 1 : 0.677725118483
+2016-08-24 12:38:45,846 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:38:45,856 DEBUG: View 3 : 0.649289099526
+2016-08-24 12:38:46,600 DEBUG: Best view : MiRNA__
+2016-08-24 12:39:06,116 DEBUG: Start: Iteration 242
+2016-08-24 12:39:06,137 DEBUG: View 0 : 0.549763033175
+2016-08-24 12:39:06,147 DEBUG: View 1 : 0.658767772512
+2016-08-24 12:39:06,265 DEBUG: View 2 : 0.535545023697
+2016-08-24 12:39:06,275 DEBUG: View 3 : 0.687203791469
+2016-08-24 12:39:07,024 DEBUG: Best view : Clinic_
+2016-08-24 12:39:26,644 DEBUG: Start: Iteration 243
+2016-08-24 12:39:26,665 DEBUG: View 0 : 0.748815165877
+2016-08-24 12:39:26,675 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:39:26,796 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:39:26,805 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:39:27,561 DEBUG: Best view : Methyl_
+2016-08-24 12:39:47,265 DEBUG: Start: Iteration 244
+2016-08-24 12:39:47,286 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:39:47,296 DEBUG: View 1 : 0.45971563981
+2016-08-24 12:39:47,413 DEBUG: View 2 : 0.620853080569
+2016-08-24 12:39:47,422 DEBUG: View 3 : 0.497630331754
+2016-08-24 12:39:48,175 DEBUG: Best view : RANSeq_
+2016-08-24 12:40:07,943 DEBUG: Start: Iteration 245
+2016-08-24 12:40:07,964 DEBUG: View 0 : 0.492890995261
+2016-08-24 12:40:07,974 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:40:08,075 DEBUG: View 2 : 0.630331753555
+2016-08-24 12:40:08,085 DEBUG: View 3 : 0.507109004739
+2016-08-24 12:40:08,845 DEBUG: Best view : RANSeq_
+2016-08-24 12:40:28,754 DEBUG: Start: Iteration 246
+2016-08-24 12:40:28,775 DEBUG: View 0 : 0.729857819905
+2016-08-24 12:40:28,785 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:40:28,902 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:40:28,911 DEBUG: View 3 : 0.677725118483
+2016-08-24 12:40:29,672 DEBUG: Best view : Methyl_
+2016-08-24 12:40:49,632 DEBUG: Start: Iteration 247
+2016-08-24 12:40:49,654 DEBUG: View 0 : 0.440758293839
+2016-08-24 12:40:49,663 DEBUG: View 1 : 0.369668246445
+2016-08-24 12:40:49,781 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:40:49,790 DEBUG: View 3 : 0.611374407583
+2016-08-24 12:40:50,557 DEBUG: Best view : Clinic_
+2016-08-24 12:41:10,634 DEBUG: Start: Iteration 248
+2016-08-24 12:41:10,653 DEBUG: View 0 : 0.592417061611
+2016-08-24 12:41:10,663 DEBUG: View 1 : 0.763033175355
+2016-08-24 12:41:10,785 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:41:10,794 DEBUG: View 3 : 0.601895734597
+2016-08-24 12:41:11,561 DEBUG: Best view : MiRNA__
+2016-08-24 12:41:31,677 DEBUG: Start: Iteration 249
+2016-08-24 12:41:31,698 DEBUG: View 0 : 0.488151658768
+2016-08-24 12:41:31,708 DEBUG: View 1 : 0.777251184834
+2016-08-24 12:41:31,832 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:41:31,841 DEBUG: View 3 : 0.545023696682
+2016-08-24 12:41:32,606 DEBUG: Best view : MiRNA__
+2016-08-24 12:41:52,512 DEBUG: Start: Iteration 250
+2016-08-24 12:41:52,533 DEBUG: View 0 : 0.635071090047
+2016-08-24 12:41:52,543 DEBUG: View 1 : 0.687203791469
+2016-08-24 12:41:52,666 DEBUG: View 2 : 0.545023696682
+2016-08-24 12:41:52,676 DEBUG: View 3 : 0.691943127962
+2016-08-24 12:41:53,438 DEBUG: Best view : Clinic_
+2016-08-24 12:42:13,324 DEBUG: Start: Iteration 251
+2016-08-24 12:42:13,346 DEBUG: View 0 : 0.620853080569
+2016-08-24 12:42:13,356 DEBUG: View 1 : 0.364928909953
+2016-08-24 12:42:13,476 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:42:13,486 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:42:14,258 DEBUG: Best view : RANSeq_
+2016-08-24 12:42:34,246 DEBUG: Start: Iteration 252
+2016-08-24 12:42:34,267 DEBUG: View 0 : 0.597156398104
+2016-08-24 12:42:34,276 DEBUG: View 1 : 0.407582938389
+2016-08-24 12:42:34,390 DEBUG: View 2 : 0.511848341232
+2016-08-24 12:42:34,400 DEBUG: View 3 : 0.492890995261
+2016-08-24 12:42:35,175 DEBUG: Best view : Methyl_
+2016-08-24 12:42:55,285 DEBUG: Start: Iteration 253
+2016-08-24 12:42:55,307 DEBUG: View 0 : 0.521327014218
+2016-08-24 12:42:55,317 DEBUG: View 1 : 0.582938388626
+2016-08-24 12:42:55,443 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:42:55,453 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:42:56,233 DEBUG: Best view : Clinic_
+2016-08-24 12:43:16,372 DEBUG: Start: Iteration 254
+2016-08-24 12:43:16,393 DEBUG: View 0 : 0.516587677725
+2016-08-24 12:43:16,403 DEBUG: View 1 : 0.473933649289
+2016-08-24 12:43:16,532 DEBUG: View 2 : 0.516587677725
+2016-08-24 12:43:16,543 DEBUG: View 3 : 0.497630331754
+2016-08-24 12:43:17,330 DEBUG: Best view : Methyl_
+2016-08-24 12:43:37,613 DEBUG: Start: Iteration 255
+2016-08-24 12:43:37,634 DEBUG: View 0 : 0.473933649289
+2016-08-24 12:43:37,644 DEBUG: View 1 : 0.63981042654
+2016-08-24 12:43:37,771 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:43:37,782 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:43:38,562 DEBUG: Best view : MiRNA__
+2016-08-24 12:43:58,879 DEBUG: Start: Iteration 256
+2016-08-24 12:43:58,900 DEBUG: View 0 : 0.469194312796
+2016-08-24 12:43:58,909 DEBUG: View 1 : 0.601895734597
+2016-08-24 12:43:59,033 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:43:59,044 DEBUG: View 3 : 0.663507109005
+2016-08-24 12:43:59,827 DEBUG: Best view : Clinic_
+2016-08-24 12:44:20,227 DEBUG: Start: Iteration 257
+2016-08-24 12:44:20,249 DEBUG: View 0 : 0.554502369668
+2016-08-24 12:44:20,259 DEBUG: View 1 : 0.625592417062
+2016-08-24 12:44:20,387 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:44:20,398 DEBUG: View 3 : 0.507109004739
+2016-08-24 12:44:21,184 DEBUG: Best view : MiRNA__
+2016-08-24 12:44:41,641 DEBUG: Start: Iteration 258
+2016-08-24 12:44:41,662 DEBUG: View 0 : 0.454976303318
+2016-08-24 12:44:41,673 DEBUG: View 1 : 0.478672985782
+2016-08-24 12:44:41,799 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:44:41,810 DEBUG: View 3 : 0.649289099526
+2016-08-24 12:44:42,597 DEBUG: Best view : Clinic_
+2016-08-24 12:45:03,175 DEBUG: Start: Iteration 259
+2016-08-24 12:45:03,196 DEBUG: View 0 : 0.625592417062
+2016-08-24 12:45:03,206 DEBUG: View 1 : 0.701421800948
+2016-08-24 12:45:03,329 DEBUG: View 2 : 0.516587677725
+2016-08-24 12:45:03,340 DEBUG: View 3 : 0.582938388626
+2016-08-24 12:45:04,129 DEBUG: Best view : MiRNA__
+2016-08-24 12:45:24,744 DEBUG: Start: Iteration 260
+2016-08-24 12:45:24,765 DEBUG: View 0 : 0.616113744076
+2016-08-24 12:45:24,774 DEBUG: View 1 : 0.625592417062
+2016-08-24 12:45:24,899 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:45:24,909 DEBUG: View 3 : 0.549763033175
+2016-08-24 12:45:25,705 DEBUG: Best view : MiRNA__
+2016-08-24 12:45:46,401 DEBUG: Start: Iteration 261
+2016-08-24 12:45:46,423 DEBUG: View 0 : 0.535545023697
+2016-08-24 12:45:46,432 DEBUG: View 1 : 0.663507109005
+2016-08-24 12:45:46,559 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:45:46,570 DEBUG: View 3 : 0.620853080569
+2016-08-24 12:45:47,370 DEBUG: Best view : MiRNA__
+2016-08-24 12:46:08,132 DEBUG: Start: Iteration 262
+2016-08-24 12:46:08,153 DEBUG: View 0 : 0.54028436019
+2016-08-24 12:46:08,163 DEBUG: View 1 : 0.620853080569
+2016-08-24 12:46:08,294 DEBUG: View 2 : 0.559241706161
+2016-08-24 12:46:08,305 DEBUG: View 3 : 0.545023696682
+2016-08-24 12:46:09,099 DEBUG: Best view : MiRNA__
+2016-08-24 12:46:29,920 DEBUG: Start: Iteration 263
+2016-08-24 12:46:29,941 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:46:29,951 DEBUG: View 1 : 0.644549763033
+2016-08-24 12:46:30,079 DEBUG: View 2 : 0.526066350711
+2016-08-24 12:46:30,090 DEBUG: View 3 : 0.611374407583
+2016-08-24 12:46:30,901 DEBUG: Best view : Clinic_
+2016-08-24 12:46:51,789 DEBUG: Start: Iteration 264
+2016-08-24 12:46:51,810 DEBUG: View 0 : 0.60663507109
+2016-08-24 12:46:51,820 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:46:51,936 DEBUG: View 2 : 0.630331753555
+2016-08-24 12:46:51,947 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:46:52,749 DEBUG: Best view : Clinic_
+2016-08-24 12:47:13,747 DEBUG: Start: Iteration 265
+2016-08-24 12:47:13,769 DEBUG: View 0 : 0.691943127962
+2016-08-24 12:47:13,778 DEBUG: View 1 : 0.402843601896
+2016-08-24 12:47:13,907 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:47:13,918 DEBUG: View 3 : 0.578199052133
+2016-08-24 12:47:14,728 DEBUG: Best view : Methyl_
+2016-08-24 12:47:35,822 DEBUG: Start: Iteration 266
+2016-08-24 12:47:35,843 DEBUG: View 0 : 0.677725118483
+2016-08-24 12:47:35,853 DEBUG: View 1 : 0.706161137441
+2016-08-24 12:47:35,975 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:47:35,985 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:47:36,793 DEBUG: Best view : MiRNA__
+2016-08-24 12:47:57,934 DEBUG: Start: Iteration 267
+2016-08-24 12:47:57,955 DEBUG: View 0 : 0.559241706161
+2016-08-24 12:47:57,964 DEBUG: View 1 : 0.744075829384
+2016-08-24 12:47:58,093 DEBUG: View 2 : 0.549763033175
+2016-08-24 12:47:58,103 DEBUG: View 3 : 0.630331753555
+2016-08-24 12:47:58,921 DEBUG: Best view : MiRNA__
+2016-08-24 12:48:20,152 DEBUG: Start: Iteration 268
+2016-08-24 12:48:20,173 DEBUG: View 0 : 0.526066350711
+2016-08-24 12:48:20,182 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:48:20,306 DEBUG: View 2 : 0.57345971564
+2016-08-24 12:48:20,316 DEBUG: View 3 : 0.701421800948
+2016-08-24 12:48:21,134 DEBUG: Best view : Clinic_
+2016-08-24 12:48:42,436 DEBUG: Start: Iteration 269
+2016-08-24 12:48:42,456 DEBUG: View 0 : 0.42654028436
+2016-08-24 12:48:42,466 DEBUG: View 1 : 0.57345971564
+2016-08-24 12:48:42,592 DEBUG: View 2 : 0.497630331754
+2016-08-24 12:48:42,602 DEBUG: View 3 : 0.611374407583
+2016-08-24 12:48:43,424 DEBUG: Best view : Clinic_
+2016-08-24 12:49:04,786 DEBUG: Start: Iteration 270
+2016-08-24 12:49:04,807 DEBUG: View 0 : 0.57345971564
+2016-08-24 12:49:04,816 DEBUG: View 1 : 0.412322274882
+2016-08-24 12:49:04,945 DEBUG: View 2 : 0.630331753555
+2016-08-24 12:49:04,956 DEBUG: View 3 : 0.478672985782
+2016-08-24 12:49:05,789 DEBUG: Best view : RANSeq_
+2016-08-24 12:49:27,239 DEBUG: Start: Iteration 271
+2016-08-24 12:49:27,260 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:49:27,270 DEBUG: View 1 : 0.521327014218
+2016-08-24 12:49:27,396 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:49:27,407 DEBUG: View 3 : 0.654028436019
+2016-08-24 12:49:28,229 DEBUG: Best view : Clinic_
+2016-08-24 12:49:49,823 DEBUG: Start: Iteration 272
+2016-08-24 12:49:49,845 DEBUG: View 0 : 0.616113744076
+2016-08-24 12:49:49,854 DEBUG: View 1 : 0.545023696682
+2016-08-24 12:49:49,981 DEBUG: View 2 : 0.611374407583
+2016-08-24 12:49:49,992 DEBUG: View 3 : 0.535545023697
+2016-08-24 12:49:50,819 DEBUG: Best view : RANSeq_
+2016-08-24 12:50:12,458 DEBUG: Start: Iteration 273
+2016-08-24 12:50:12,480 DEBUG: View 0 : 0.502369668246
+2016-08-24 12:50:12,489 DEBUG: View 1 : 0.635071090047
+2016-08-24 12:50:12,618 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:50:12,628 DEBUG: View 3 : 0.507109004739
+2016-08-24 12:50:13,463 DEBUG: Best view : MiRNA__
+2016-08-24 12:50:35,159 DEBUG: Start: Iteration 274
+2016-08-24 12:50:35,180 DEBUG: View 0 : 0.436018957346
+2016-08-24 12:50:35,189 DEBUG: View 1 : 0.587677725118
+2016-08-24 12:50:35,317 DEBUG: View 2 : 0.601895734597
+2016-08-24 12:50:35,328 DEBUG: View 3 : 0.554502369668
+2016-08-24 12:50:36,162 DEBUG: Best view : RANSeq_
+2016-08-24 12:50:57,942 DEBUG: Start: Iteration 275
+2016-08-24 12:50:57,963 DEBUG: View 0 : 0.473933649289
+2016-08-24 12:50:57,973 DEBUG: View 1 : 0.658767772512
+2016-08-24 12:50:58,092 DEBUG: View 2 : 0.526066350711
+2016-08-24 12:50:58,102 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:50:58,936 DEBUG: Best view : MiRNA__
+2016-08-24 12:51:20,806 DEBUG: Start: Iteration 276
+2016-08-24 12:51:20,827 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:51:20,837 DEBUG: View 1 : 0.729857819905
+2016-08-24 12:51:20,957 DEBUG: View 2 : 0.511848341232
+2016-08-24 12:51:20,968 DEBUG: View 3 : 0.57345971564
+2016-08-24 12:51:21,806 DEBUG: Best view : MiRNA__
+2016-08-24 12:51:43,736 DEBUG: Start: Iteration 277
+2016-08-24 12:51:43,757 DEBUG: View 0 : 0.464454976303
+2016-08-24 12:51:43,767 DEBUG: View 1 : 0.668246445498
+2016-08-24 12:51:43,893 DEBUG: View 2 : 0.654028436019
+2016-08-24 12:51:43,903 DEBUG: View 3 : 0.582938388626
+2016-08-24 12:51:44,745 DEBUG: Best view : RANSeq_
+2016-08-24 12:52:06,799 DEBUG: Start: Iteration 278
+2016-08-24 12:52:06,820 DEBUG: View 0 : 0.526066350711
+2016-08-24 12:52:06,830 DEBUG: View 1 : 0.706161137441
+2016-08-24 12:52:06,956 DEBUG: View 2 : 0.563981042654
+2016-08-24 12:52:06,966 DEBUG: View 3 : 0.563981042654
+2016-08-24 12:52:07,817 DEBUG: Best view : MiRNA__
+2016-08-24 12:52:29,952 DEBUG: Start: Iteration 279
+2016-08-24 12:52:29,973 DEBUG: View 0 : 0.644549763033
+2016-08-24 12:52:29,983 DEBUG: View 1 : 0.473933649289
+2016-08-24 12:52:30,112 DEBUG: View 2 : 0.597156398104
+2016-08-24 12:52:30,123 DEBUG: View 3 : 0.630331753555
+2016-08-24 12:52:30,970 DEBUG: Best view : Methyl_
+2016-08-24 12:52:53,162 DEBUG: Start: Iteration 280
+2016-08-24 12:52:53,183 DEBUG: View 0 : 0.521327014218
+2016-08-24 12:52:53,193 DEBUG: View 1 : 0.379146919431
+2016-08-24 12:52:53,322 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:52:53,333 DEBUG: View 3 : 0.658767772512
+2016-08-24 12:52:54,181 DEBUG: Best view : Clinic_
+2016-08-24 12:53:16,493 DEBUG: Start: Iteration 281
+2016-08-24 12:53:16,514 DEBUG: View 0 : 0.559241706161
+2016-08-24 12:53:16,524 DEBUG: View 1 : 0.60663507109
+2016-08-24 12:53:16,648 DEBUG: View 2 : 0.521327014218
+2016-08-24 12:53:16,659 DEBUG: View 3 : 0.60663507109
+2016-08-24 12:53:17,515 DEBUG: Best view : Clinic_
+2016-08-24 12:53:39,938 DEBUG: Start: Iteration 282
+2016-08-24 12:53:39,959 DEBUG: View 0 : 0.568720379147
+2016-08-24 12:53:39,969 DEBUG: View 1 : 0.317535545024
+2016-08-24 12:53:40,093 DEBUG: View 2 : 0.625592417062
+2016-08-24 12:53:40,104 DEBUG: View 3 : 0.654028436019
+2016-08-24 12:53:40,961 DEBUG: Best view : Clinic_
+2016-08-24 12:54:03,344 DEBUG: Start: Iteration 283
+2016-08-24 12:54:03,366 DEBUG: View 0 : 0.521327014218
+2016-08-24 12:54:03,375 DEBUG: View 1 : 0.578199052133
+2016-08-24 12:54:03,496 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:54:03,506 DEBUG: View 3 : 0.701421800948
+2016-08-24 12:54:04,364 DEBUG: Best view : Clinic_
+2016-08-24 12:54:26,851 DEBUG: Start: Iteration 284
+2016-08-24 12:54:26,872 DEBUG: View 0 : 0.630331753555
+2016-08-24 12:54:26,882 DEBUG: View 1 : 0.63981042654
+2016-08-24 12:54:27,010 DEBUG: View 2 : 0.60663507109
+2016-08-24 12:54:27,021 DEBUG: View 3 : 0.616113744076
+2016-08-24 12:54:27,891 DEBUG: Best view : MiRNA__
+2016-08-24 12:54:50,442 DEBUG: Start: Iteration 285
+2016-08-24 12:54:50,463 DEBUG: View 0 : 0.469194312796
+2016-08-24 12:54:50,473 DEBUG: View 1 : 0.635071090047
+2016-08-24 12:54:50,598 DEBUG: View 2 : 0.507109004739
+2016-08-24 12:54:50,609 DEBUG: View 3 : 0.592417061611
+2016-08-24 12:54:51,471 DEBUG: Best view : MiRNA__
+2016-08-24 12:55:14,160 DEBUG: Start: Iteration 286
+2016-08-24 12:55:14,181 DEBUG: View 0 : 0.497630331754
+2016-08-24 12:55:14,190 DEBUG: View 1 : 0.597156398104
+2016-08-24 12:55:14,316 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:55:14,326 DEBUG: View 3 : 0.635071090047
+2016-08-24 12:55:15,212 DEBUG: Best view : Clinic_
+2016-08-24 12:55:37,935 DEBUG: Start: Iteration 287
+2016-08-24 12:55:37,954 DEBUG: View 0 : 0.398104265403
+2016-08-24 12:55:37,964 DEBUG: View 1 : 0.445497630332
+2016-08-24 12:55:38,095 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:55:38,106 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:55:38,977 DEBUG: Best view : Clinic_
+2016-08-24 12:56:01,705 DEBUG: Start: Iteration 288
+2016-08-24 12:56:01,726 DEBUG: View 0 : 0.597156398104
+2016-08-24 12:56:01,735 DEBUG: View 1 : 0.483412322275
+2016-08-24 12:56:01,866 DEBUG: View 2 : 0.530805687204
+2016-08-24 12:56:01,877 DEBUG: View 3 : 0.492890995261
+2016-08-24 12:56:02,747 DEBUG: Best view : Methyl_
+2016-08-24 12:56:25,635 DEBUG: Start: Iteration 289
+2016-08-24 12:56:25,656 DEBUG: View 0 : 0.530805687204
+2016-08-24 12:56:25,665 DEBUG: View 1 : 0.644549763033
+2016-08-24 12:56:25,792 DEBUG: View 2 : 0.568720379147
+2016-08-24 12:56:25,804 DEBUG: View 3 : 0.625592417062
+2016-08-24 12:56:26,676 DEBUG: Best view : Clinic_
+2016-08-24 12:56:49,632 DEBUG: Start: Iteration 290
+2016-08-24 12:56:49,653 DEBUG: View 0 : 0.497630331754
+2016-08-24 12:56:49,663 DEBUG: View 1 : 0.582938388626
+2016-08-24 12:56:49,798 DEBUG: View 2 : 0.554502369668
+2016-08-24 12:56:49,809 DEBUG: View 3 : 0.563981042654
+2016-08-24 12:56:50,683 DEBUG: Best view : Clinic_
+2016-08-24 12:57:13,765 DEBUG: Start: Iteration 291
+2016-08-24 12:57:13,786 DEBUG: View 0 : 0.483412322275
+2016-08-24 12:57:13,796 DEBUG: View 1 : 0.412322274882
+2016-08-24 12:57:13,930 DEBUG: View 2 : 0.592417061611
+2016-08-24 12:57:13,942 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:57:14,822 DEBUG: Best view : RANSeq_
+2016-08-24 12:57:37,933 DEBUG: Start: Iteration 292
+2016-08-24 12:57:37,955 DEBUG: View 0 : 0.511848341232
+2016-08-24 12:57:37,964 DEBUG: View 1 : 0.445497630332
+2016-08-24 12:57:38,094 DEBUG: View 2 : 0.620853080569
+2016-08-24 12:57:38,106 DEBUG: View 3 : 0.601895734597
+2016-08-24 12:57:38,988 DEBUG: Best view : RANSeq_
+2016-08-24 12:58:02,193 DEBUG: Start: Iteration 293
+2016-08-24 12:58:02,215 DEBUG: View 0 : 0.578199052133
+2016-08-24 12:58:02,225 DEBUG: View 1 : 0.454976303318
+2016-08-24 12:58:02,357 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:58:02,368 DEBUG: View 3 : 0.625592417062
+2016-08-24 12:58:03,251 DEBUG: Best view : Clinic_
+2016-08-24 12:58:26,533 DEBUG: Start: Iteration 294
+2016-08-24 12:58:26,554 DEBUG: View 0 : 0.597156398104
+2016-08-24 12:58:26,564 DEBUG: View 1 : 0.39336492891
+2016-08-24 12:58:26,688 DEBUG: View 2 : 0.57345971564
+2016-08-24 12:58:26,699 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:58:27,585 DEBUG: Best view : Clinic_
+2016-08-24 12:58:50,953 DEBUG: Start: Iteration 295
+2016-08-24 12:58:50,974 DEBUG: View 0 : 0.488151658768
+2016-08-24 12:58:50,984 DEBUG: View 1 : 0.715639810427
+2016-08-24 12:58:51,111 DEBUG: View 2 : 0.582938388626
+2016-08-24 12:58:51,122 DEBUG: View 3 : 0.568720379147
+2016-08-24 12:58:52,015 DEBUG: Best view : MiRNA__
+2016-08-24 12:59:15,436 DEBUG: Start: Iteration 296
+2016-08-24 12:59:15,457 DEBUG: View 0 : 0.507109004739
+2016-08-24 12:59:15,466 DEBUG: View 1 : 0.530805687204
+2016-08-24 12:59:15,594 DEBUG: View 2 : 0.587677725118
+2016-08-24 12:59:15,604 DEBUG: View 3 : 0.597156398104
+2016-08-24 12:59:16,503 DEBUG: Best view : Clinic_
+2016-08-24 12:59:40,003 DEBUG: Start: Iteration 297
+2016-08-24 12:59:40,024 DEBUG: View 0 : 0.563981042654
+2016-08-24 12:59:40,033 DEBUG: View 1 : 0.582938388626
+2016-08-24 12:59:40,159 DEBUG: View 2 : 0.578199052133
+2016-08-24 12:59:40,169 DEBUG: View 3 : 0.530805687204
+2016-08-24 12:59:41,074 DEBUG: Best view : RANSeq_
+2016-08-24 13:00:04,679 DEBUG: Start: Iteration 298
+2016-08-24 13:00:04,700 DEBUG: View 0 : 0.440758293839
+2016-08-24 13:00:04,709 DEBUG: View 1 : 0.545023696682
+2016-08-24 13:00:04,837 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:00:04,847 DEBUG: View 3 : 0.658767772512
+2016-08-24 13:00:05,752 DEBUG: Best view : Clinic_
+2016-08-24 13:00:29,468 DEBUG: Start: Iteration 299
+2016-08-24 13:00:29,489 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:00:29,498 DEBUG: View 1 : 0.440758293839
+2016-08-24 13:00:29,623 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:00:29,634 DEBUG: View 3 : 0.620853080569
+2016-08-24 13:00:30,543 DEBUG: Best view : Clinic_
+2016-08-24 13:00:54,312 DEBUG: Start: Iteration 300
+2016-08-24 13:00:54,334 DEBUG: View 0 : 0.587677725118
+2016-08-24 13:00:54,343 DEBUG: View 1 : 0.549763033175
+2016-08-24 13:00:54,474 DEBUG: View 2 : 0.60663507109
+2016-08-24 13:00:54,485 DEBUG: View 3 : 0.568720379147
+2016-08-24 13:00:55,389 DEBUG: Best view : RANSeq_
+2016-08-24 13:01:19,318 DEBUG: Start: Iteration 301
+2016-08-24 13:01:19,339 DEBUG: View 0 : 0.511848341232
+2016-08-24 13:01:19,349 DEBUG: View 1 : 0.60663507109
+2016-08-24 13:01:19,478 DEBUG: View 2 : 0.630331753555
+2016-08-24 13:01:19,489 DEBUG: View 3 : 0.549763033175
+2016-08-24 13:01:20,406 DEBUG: Best view : RANSeq_
+2016-08-24 13:01:44,342 DEBUG: Start: Iteration 302
+2016-08-24 13:01:44,363 DEBUG: View 0 : 0.507109004739
+2016-08-24 13:01:44,373 DEBUG: View 1 : 0.611374407583
+2016-08-24 13:01:44,499 DEBUG: View 2 : 0.554502369668
+2016-08-24 13:01:44,510 DEBUG: View 3 : 0.57345971564
+2016-08-24 13:01:45,420 DEBUG: Best view : Clinic_
+2016-08-24 13:02:09,473 DEBUG: Start: Iteration 303
+2016-08-24 13:02:09,494 DEBUG: View 0 : 0.663507109005
+2016-08-24 13:02:09,504 DEBUG: View 1 : 0.554502369668
+2016-08-24 13:02:09,629 DEBUG: View 2 : 0.530805687204
+2016-08-24 13:02:09,640 DEBUG: View 3 : 0.549763033175
+2016-08-24 13:02:10,560 DEBUG: Best view : Methyl_
+2016-08-24 13:02:34,701 DEBUG: Start: Iteration 304
+2016-08-24 13:02:34,722 DEBUG: View 0 : 0.597156398104
+2016-08-24 13:02:34,732 DEBUG: View 1 : 0.729857819905
+2016-08-24 13:02:34,853 DEBUG: View 2 : 0.587677725118
+2016-08-24 13:02:34,864 DEBUG: View 3 : 0.620853080569
+2016-08-24 13:02:35,788 DEBUG: Best view : MiRNA__
+2016-08-24 13:02:59,937 DEBUG: Start: Iteration 305
+2016-08-24 13:02:59,958 DEBUG: View 0 : 0.473933649289
+2016-08-24 13:02:59,968 DEBUG: View 1 : 0.601895734597
+2016-08-24 13:03:00,090 DEBUG: View 2 : 0.625592417062
+2016-08-24 13:03:00,101 DEBUG: View 3 : 0.516587677725
+2016-08-24 13:03:01,023 DEBUG: Best view : RANSeq_
+2016-08-24 13:03:25,286 DEBUG: Start: Iteration 306
+2016-08-24 13:03:25,307 DEBUG: View 0 : 0.454976303318
+2016-08-24 13:03:25,317 DEBUG: View 1 : 0.710900473934
+2016-08-24 13:03:25,451 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:03:25,461 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:03:26,384 DEBUG: Best view : MiRNA__
+2016-08-24 13:03:50,762 DEBUG: Start: Iteration 307
+2016-08-24 13:03:50,783 DEBUG: View 0 : 0.644549763033
+2016-08-24 13:03:50,793 DEBUG: View 1 : 0.611374407583
+2016-08-24 13:03:50,921 DEBUG: View 2 : 0.511848341232
+2016-08-24 13:03:50,932 DEBUG: View 3 : 0.635071090047
+2016-08-24 13:03:51,861 DEBUG: Best view : Clinic_
+2016-08-24 13:04:16,296 DEBUG: Start: Iteration 308
+2016-08-24 13:04:16,317 DEBUG: View 0 : 0.582938388626
+2016-08-24 13:04:16,326 DEBUG: View 1 : 0.677725118483
+2016-08-24 13:04:16,452 DEBUG: View 2 : 0.54028436019
+2016-08-24 13:04:16,463 DEBUG: View 3 : 0.582938388626
+2016-08-24 13:04:17,396 DEBUG: Best view : MiRNA__
+2016-08-24 13:04:41,935 DEBUG: Start: Iteration 309
+2016-08-24 13:04:41,954 DEBUG: View 0 : 0.530805687204
+2016-08-24 13:04:41,964 DEBUG: View 1 : 0.63981042654
+2016-08-24 13:04:42,095 DEBUG: View 2 : 0.549763033175
+2016-08-24 13:04:42,106 DEBUG: View 3 : 0.54028436019
+2016-08-24 13:04:43,048 DEBUG: Best view : MiRNA__
+2016-08-24 13:05:07,600 DEBUG: Start: Iteration 310
+2016-08-24 13:05:07,621 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:05:07,632 DEBUG: View 1 : 0.592417061611
+2016-08-24 13:05:07,760 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:05:07,771 DEBUG: View 3 : 0.554502369668
+2016-08-24 13:05:08,706 DEBUG: Best view : Methyl_
+2016-08-24 13:05:33,385 DEBUG: Start: Iteration 311
+2016-08-24 13:05:33,406 DEBUG: View 0 : 0.81990521327
+2016-08-24 13:05:33,416 DEBUG: View 1 : 0.644549763033
+2016-08-24 13:05:33,542 DEBUG: View 2 : 0.521327014218
+2016-08-24 13:05:33,552 DEBUG: View 3 : 0.601895734597
+2016-08-24 13:05:34,490 DEBUG: Best view : Methyl_
+2016-08-24 13:05:59,216 DEBUG: Start: Iteration 312
+2016-08-24 13:05:59,237 DEBUG: View 0 : 0.440758293839
+2016-08-24 13:05:59,246 DEBUG: View 1 : 0.578199052133
+2016-08-24 13:05:59,373 DEBUG: View 2 : 0.545023696682
+2016-08-24 13:05:59,384 DEBUG: View 3 : 0.682464454976
+2016-08-24 13:06:00,326 DEBUG: Best view : Clinic_
+2016-08-24 13:06:25,148 DEBUG: Start: Iteration 313
+2016-08-24 13:06:25,169 DEBUG: View 0 : 0.597156398104
+2016-08-24 13:06:25,179 DEBUG: View 1 : 0.715639810427
+2016-08-24 13:06:25,314 DEBUG: View 2 : 0.535545023697
+2016-08-24 13:06:25,325 DEBUG: View 3 : 0.672985781991
+2016-08-24 13:06:26,268 DEBUG: Best view : MiRNA__
+2016-08-24 13:06:51,146 DEBUG: Start: Iteration 314
+2016-08-24 13:06:51,167 DEBUG: View 0 : 0.563981042654
+2016-08-24 13:06:51,176 DEBUG: View 1 : 0.620853080569
+2016-08-24 13:06:51,304 DEBUG: View 2 : 0.663507109005
+2016-08-24 13:06:51,315 DEBUG: View 3 : 0.611374407583
+2016-08-24 13:06:52,260 DEBUG: Best view : RANSeq_
+2016-08-24 13:07:17,317 DEBUG: Start: Iteration 315
+2016-08-24 13:07:17,338 DEBUG: View 0 : 0.568720379147
+2016-08-24 13:07:17,348 DEBUG: View 1 : 0.379146919431
+2016-08-24 13:07:17,474 DEBUG: View 2 : 0.582938388626
+2016-08-24 13:07:17,485 DEBUG: View 3 : 0.568720379147
+2016-08-24 13:07:18,436 DEBUG: Best view : RANSeq_
+2016-08-24 13:07:43,598 DEBUG: Start: Iteration 316
+2016-08-24 13:07:43,619 DEBUG: View 0 : 0.407582938389
+2016-08-24 13:07:43,629 DEBUG: View 1 : 0.545023696682
+2016-08-24 13:07:43,759 DEBUG: View 2 : 0.592417061611
+2016-08-24 13:07:43,770 DEBUG: View 3 : 0.710900473934
+2016-08-24 13:07:44,721 DEBUG: Best view : Clinic_
+2016-08-24 13:08:09,887 DEBUG: Start: Iteration 317
+2016-08-24 13:08:09,908 DEBUG: View 0 : 0.696682464455
+2016-08-24 13:08:09,918 DEBUG: View 1 : 0.625592417062
+2016-08-24 13:08:10,041 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:08:10,052 DEBUG: View 3 : 0.682464454976
+2016-08-24 13:08:11,006 DEBUG: Best view : Methyl_
+2016-08-24 13:08:36,231 DEBUG: Start: Iteration 318
+2016-08-24 13:08:36,252 DEBUG: View 0 : 0.63981042654
+2016-08-24 13:08:36,261 DEBUG: View 1 : 0.611374407583
+2016-08-24 13:08:36,388 DEBUG: View 2 : 0.535545023697
+2016-08-24 13:08:36,399 DEBUG: View 3 : 0.57345971564
+2016-08-24 13:08:37,367 DEBUG: Best view : Methyl_
+2016-08-24 13:09:02,676 DEBUG: Start: Iteration 319
+2016-08-24 13:09:02,697 DEBUG: View 0 : 0.701421800948
+2016-08-24 13:09:02,706 DEBUG: View 1 : 0.597156398104
+2016-08-24 13:09:02,833 DEBUG: View 2 : 0.497630331754
+2016-08-24 13:09:02,844 DEBUG: View 3 : 0.530805687204
+2016-08-24 13:09:03,803 DEBUG: Best view : Methyl_
+2016-08-24 13:09:29,304 DEBUG: Start: Iteration 320
+2016-08-24 13:09:29,325 DEBUG: View 0 : 0.516587677725
+2016-08-24 13:09:29,335 DEBUG: View 1 : 0.625592417062
+2016-08-24 13:09:29,462 DEBUG: View 2 : 0.545023696682
+2016-08-24 13:09:29,473 DEBUG: View 3 : 0.578199052133
+2016-08-24 13:09:30,442 DEBUG: Best view : Clinic_
+2016-08-24 13:09:55,977 DEBUG: Start: Iteration 321
+2016-08-24 13:09:55,998 DEBUG: View 0 : 0.611374407583
+2016-08-24 13:09:56,008 DEBUG: View 1 : 0.492890995261
+2016-08-24 13:09:56,129 DEBUG: View 2 : 0.492890995261
+2016-08-24 13:09:56,140 DEBUG: View 3 : 0.60663507109
+2016-08-24 13:09:57,108 DEBUG: Best view : Clinic_
+2016-08-24 13:10:22,680 DEBUG: Start: Iteration 322
+2016-08-24 13:10:22,699 DEBUG: View 0 : 0.502369668246
+2016-08-24 13:10:22,709 DEBUG: View 1 : 0.644549763033
+2016-08-24 13:10:22,836 DEBUG: View 2 : 0.497630331754
+2016-08-24 13:10:22,847 DEBUG: View 3 : 0.682464454976
+2016-08-24 13:10:23,824 DEBUG: Best view : Clinic_
+2016-08-24 13:10:49,464 DEBUG: Start: Iteration 323
+2016-08-24 13:10:49,485 DEBUG: View 0 : 0.464454976303
+2016-08-24 13:10:49,495 DEBUG: View 1 : 0.445497630332
+2016-08-24 13:10:49,627 DEBUG: View 2 : 0.597156398104
+2016-08-24 13:10:49,638 DEBUG: View 3 : 0.63981042654
+2016-08-24 13:10:50,603 DEBUG: Best view : Clinic_
+2016-08-24 13:11:16,319 DEBUG: Start: Iteration 324
+2016-08-24 13:11:16,340 DEBUG: View 0 : 0.545023696682
+2016-08-24 13:11:16,350 DEBUG: View 1 : 0.701421800948
+2016-08-24 13:11:16,481 DEBUG: View 2 : 0.57345971564
+2016-08-24 13:11:16,492 DEBUG: View 3 : 0.478672985782
+2016-08-24 13:11:17,473 DEBUG: Best view : MiRNA__
+2016-08-24 13:11:43,320 DEBUG: Start: Iteration 325
+2016-08-24 13:11:43,341 DEBUG: View 0 : 0.587677725118
+2016-08-24 13:11:43,351 DEBUG: View 1 : 0.649289099526
+2016-08-24 13:11:43,469 DEBUG: View 2 : 0.488151658768
+2016-08-24 13:11:43,480 DEBUG: View 3 : 0.63981042654
+2016-08-24 13:11:44,462 DEBUG: Best view : Clinic_
+2016-08-24 13:12:10,284 DEBUG: Start: Iteration 326
+2016-08-24 13:12:10,305 DEBUG: View 0 : 0.57345971564
+2016-08-24 13:12:10,315 DEBUG: View 1 : 0.729857819905
+2016-08-24 13:12:10,445 DEBUG: View 2 : 0.616113744076
+2016-08-24 13:12:10,457 DEBUG: View 3 : 0.677725118483
+2016-08-24 13:12:11,437 DEBUG: Best view : MiRNA__
+2016-08-24 13:12:37,412 DEBUG: Start: Iteration 327
+2016-08-24 13:12:37,433 DEBUG: View 0 : 0.630331753555
+2016-08-24 13:12:37,442 DEBUG: View 1 : 0.620853080569
+2016-08-24 13:12:37,574 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:12:37,585 DEBUG: View 3 : 0.559241706161
+2016-08-24 13:12:38,570 DEBUG: Best view : MiRNA__
+2016-08-24 13:13:04,614 DEBUG: Start: Iteration 328
+2016-08-24 13:13:04,635 DEBUG: View 0 : 0.592417061611
+2016-08-24 13:13:04,645 DEBUG: View 1 : 0.60663507109
+2016-08-24 13:13:04,781 DEBUG: View 2 : 0.597156398104
+2016-08-24 13:13:04,792 DEBUG: View 3 : 0.620853080569
+2016-08-24 13:13:05,777 DEBUG: Best view : Clinic_
+2016-08-24 13:13:31,866 DEBUG: Start: Iteration 329
+2016-08-24 13:13:31,887 DEBUG: View 0 : 0.582938388626
+2016-08-24 13:13:31,896 DEBUG: View 1 : 0.635071090047
+2016-08-24 13:13:32,023 DEBUG: View 2 : 0.488151658768
+2016-08-24 13:13:32,035 DEBUG: View 3 : 0.60663507109
+2016-08-24 13:13:33,028 DEBUG: Best view : Clinic_
+2016-08-24 13:13:59,177 DEBUG: Start: Iteration 330
+2016-08-24 13:13:59,198 DEBUG: View 0 : 0.492890995261
+2016-08-24 13:13:59,208 DEBUG: View 1 : 0.620853080569
+2016-08-24 13:13:59,338 DEBUG: View 2 : 0.630331753555
+2016-08-24 13:13:59,350 DEBUG: View 3 : 0.483412322275
+2016-08-24 13:14:00,344 DEBUG: Best view : RANSeq_
+2016-08-24 13:14:26,647 DEBUG: Start: Iteration 331
+2016-08-24 13:14:26,668 DEBUG: View 0 : 0.597156398104
+2016-08-24 13:14:26,677 DEBUG: View 1 : 0.630331753555
+2016-08-24 13:14:26,812 DEBUG: View 2 : 0.63981042654
+2016-08-24 13:14:26,824 DEBUG: View 3 : 0.511848341232
+2016-08-24 13:14:27,820 DEBUG: Best view : RANSeq_
+2016-08-24 13:14:54,213 DEBUG: Start: Iteration 332
+2016-08-24 13:14:54,234 DEBUG: View 0 : 0.421800947867
+2016-08-24 13:14:54,243 DEBUG: View 1 : 0.507109004739
+2016-08-24 13:14:54,382 DEBUG: View 2 : 0.625592417062
+2016-08-24 13:14:54,394 DEBUG: View 3 : 0.526066350711
+2016-08-24 13:14:55,386 DEBUG: Best view : RANSeq_
+2016-08-24 13:15:21,825 DEBUG: Start: Iteration 333
+2016-08-24 13:15:21,846 DEBUG: View 0 : 0.582938388626
+2016-08-24 13:15:21,856 DEBUG: View 1 : 0.677725118483
+2016-08-24 13:15:21,980 DEBUG: View 2 : 0.497630331754
+2016-08-24 13:15:21,992 DEBUG: View 3 : 0.682464454976
+2016-08-24 13:15:22,993 DEBUG: Best view : Clinic_
+2016-08-24 13:15:49,454 DEBUG: Start: Iteration 334
+2016-08-24 13:15:49,475 DEBUG: View 0 : 0.644549763033
+2016-08-24 13:15:49,485 DEBUG: View 1 : 0.630331753555
+2016-08-24 13:15:49,616 DEBUG: View 2 : 0.545023696682
+2016-08-24 13:15:49,627 DEBUG: View 3 : 0.682464454976
+2016-08-24 13:15:50,634 DEBUG: Best view : Clinic_
+2016-08-24 13:16:17,257 DEBUG: Start: Iteration 335
+2016-08-24 13:16:17,278 DEBUG: View 0 : 0.582938388626
+2016-08-24 13:16:17,288 DEBUG: View 1 : 0.497630331754
+2016-08-24 13:16:17,429 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:16:17,441 DEBUG: View 3 : 0.578199052133
+2016-08-24 13:16:18,444 DEBUG: Best view : Clinic_
+2016-08-24 13:16:45,102 DEBUG: Start: Iteration 336
+2016-08-24 13:16:45,123 DEBUG: View 0 : 0.772511848341
+2016-08-24 13:16:45,132 DEBUG: View 1 : 0.592417061611
+2016-08-24 13:16:45,262 DEBUG: View 2 : 0.497630331754
+2016-08-24 13:16:45,272 DEBUG: View 3 : 0.535545023697
+2016-08-24 13:16:46,283 DEBUG: Best view : Methyl_
+2016-08-24 13:17:12,988 DEBUG: Start: Iteration 337
+2016-08-24 13:17:13,009 DEBUG: View 0 : 0.45971563981
+2016-08-24 13:17:13,018 DEBUG: View 1 : 0.843601895735
+2016-08-24 13:17:13,155 DEBUG: View 2 : 0.521327014218
+2016-08-24 13:17:13,164 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:17:14,174 DEBUG: Best view : MiRNA__
+2016-08-24 13:17:40,947 DEBUG: Start: Iteration 338
+2016-08-24 13:17:40,968 DEBUG: View 0 : 0.578199052133
+2016-08-24 13:17:40,978 DEBUG: View 1 : 0.701421800948
+2016-08-24 13:17:41,102 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:17:41,111 DEBUG: View 3 : 0.625592417062
+2016-08-24 13:17:42,125 DEBUG: Best view : MiRNA__
+2016-08-24 13:18:08,964 DEBUG: Start: Iteration 339
+2016-08-24 13:18:08,985 DEBUG: View 0 : 0.445497630332
+2016-08-24 13:18:08,995 DEBUG: View 1 : 0.691943127962
+2016-08-24 13:18:09,116 DEBUG: View 2 : 0.592417061611
+2016-08-24 13:18:09,126 DEBUG: View 3 : 0.630331753555
+2016-08-24 13:18:10,144 DEBUG: Best view : MiRNA__
+2016-08-24 13:18:37,137 DEBUG: Start: Iteration 340
+2016-08-24 13:18:37,158 DEBUG: View 0 : 0.516587677725
+2016-08-24 13:18:37,168 DEBUG: View 1 : 0.829383886256
+2016-08-24 13:18:37,289 DEBUG: View 2 : 0.630331753555
+2016-08-24 13:18:37,298 DEBUG: View 3 : 0.535545023697
+2016-08-24 13:18:38,321 DEBUG: Best view : MiRNA__
+2016-08-24 13:19:05,398 DEBUG: Start: Iteration 341
+2016-08-24 13:19:05,419 DEBUG: View 0 : 0.54028436019
+2016-08-24 13:19:05,429 DEBUG: View 1 : 0.687203791469
+2016-08-24 13:19:05,558 DEBUG: View 2 : 0.54028436019
+2016-08-24 13:19:05,567 DEBUG: View 3 : 0.682464454976
+2016-08-24 13:19:06,592 DEBUG: Best view : Clinic_
+2016-08-24 13:19:33,682 DEBUG: Start: Iteration 342
+2016-08-24 13:19:33,703 DEBUG: View 0 : 0.526066350711
+2016-08-24 13:19:33,712 DEBUG: View 1 : 0.398104265403
+2016-08-24 13:19:33,846 DEBUG: View 2 : 0.526066350711
+2016-08-24 13:19:33,855 DEBUG: View 3 : 0.677725118483
+2016-08-24 13:19:34,880 DEBUG: Best view : Clinic_
+2016-08-24 13:20:02,169 DEBUG: Start: Iteration 343
+2016-08-24 13:20:02,190 DEBUG: View 0 : 0.421800947867
+2016-08-24 13:20:02,200 DEBUG: View 1 : 0.350710900474
+2016-08-24 13:20:02,331 DEBUG: View 2 : 0.535545023697
+2016-08-24 13:20:02,340 DEBUG: View 3 : 0.554502369668
+2016-08-24 13:20:03,376 DEBUG: Best view : Clinic_
+2016-08-24 13:20:31,151 DEBUG: Start: Iteration 344
+2016-08-24 13:20:31,173 DEBUG: View 0 : 0.616113744076
+2016-08-24 13:20:31,182 DEBUG: View 1 : 0.715639810427
+2016-08-24 13:20:31,302 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:20:31,312 DEBUG: View 3 : 0.625592417062
+2016-08-24 13:20:32,370 DEBUG: Best view : MiRNA__
+2016-08-24 13:21:00,542 DEBUG: Start: Iteration 345
+2016-08-24 13:21:00,564 DEBUG: View 0 : 0.436018957346
+2016-08-24 13:21:00,575 DEBUG: View 1 : 0.578199052133
+2016-08-24 13:21:00,701 DEBUG: View 2 : 0.530805687204
+2016-08-24 13:21:00,711 DEBUG: View 3 : 0.620853080569
+2016-08-24 13:21:01,779 DEBUG: Best view : Clinic_
+2016-08-24 13:21:29,765 DEBUG: Start: Iteration 346
+2016-08-24 13:21:29,786 DEBUG: View 0 : 0.63981042654
+2016-08-24 13:21:29,796 DEBUG: View 1 : 0.473933649289
+2016-08-24 13:21:29,922 DEBUG: View 2 : 0.592417061611
+2016-08-24 13:21:29,931 DEBUG: View 3 : 0.691943127962
+2016-08-24 13:21:30,995 DEBUG: Best view : Clinic_
+2016-08-24 13:21:59,180 DEBUG: Start: Iteration 347
+2016-08-24 13:21:59,201 DEBUG: View 0 : 0.587677725118
+2016-08-24 13:21:59,211 DEBUG: View 1 : 0.687203791469
+2016-08-24 13:21:59,335 DEBUG: View 2 : 0.54028436019
+2016-08-24 13:21:59,345 DEBUG: View 3 : 0.611374407583
+2016-08-24 13:22:00,434 DEBUG: Best view : MiRNA__
+2016-08-24 13:22:28,518 DEBUG: Start: Iteration 348
+2016-08-24 13:22:28,539 DEBUG: View 0 : 0.521327014218
+2016-08-24 13:22:28,549 DEBUG: View 1 : 0.563981042654
+2016-08-24 13:22:28,662 DEBUG: View 2 : 0.635071090047
+2016-08-24 13:22:28,672 DEBUG: View 3 : 0.545023696682
+2016-08-24 13:22:29,716 DEBUG: Best view : RANSeq_
+2016-08-24 13:22:57,657 DEBUG: Start: Iteration 349
+2016-08-24 13:22:57,678 DEBUG: View 0 : 0.601895734597
+2016-08-24 13:22:57,687 DEBUG: View 1 : 0.255924170616
+2016-08-24 13:22:57,819 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:22:57,829 DEBUG: View 3 : 0.45971563981
+2016-08-24 13:22:58,880 DEBUG: Best view : Methyl_
+2016-08-24 13:23:26,842 DEBUG: Start: Iteration 350
+2016-08-24 13:23:26,863 DEBUG: View 0 : 0.559241706161
+2016-08-24 13:23:26,873 DEBUG: View 1 : 0.526066350711
+2016-08-24 13:23:26,995 DEBUG: View 2 : 0.545023696682
+2016-08-24 13:23:27,006 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:23:28,055 DEBUG: Best view : Clinic_
+2016-08-24 13:23:56,069 DEBUG: Start: Iteration 351
+2016-08-24 13:23:56,090 DEBUG: View 0 : 0.563981042654
+2016-08-24 13:23:56,099 DEBUG: View 1 : 0.597156398104
+2016-08-24 13:23:56,229 DEBUG: View 2 : 0.554502369668
+2016-08-24 13:23:56,241 DEBUG: View 3 : 0.611374407583
+2016-08-24 13:23:57,313 DEBUG: Best view : Clinic_
+2016-08-24 13:24:25,267 DEBUG: Start: Iteration 352
+2016-08-24 13:24:25,288 DEBUG: View 0 : 0.658767772512
+2016-08-24 13:24:25,297 DEBUG: View 1 : 0.668246445498
+2016-08-24 13:24:25,435 DEBUG: View 2 : 0.63981042654
+2016-08-24 13:24:25,446 DEBUG: View 3 : 0.691943127962
+2016-08-24 13:24:26,503 DEBUG: Best view : Clinic_
+2016-08-24 13:24:55,334 DEBUG: Start: Iteration 353
+2016-08-24 13:24:55,356 DEBUG: View 0 : 0.715639810427
+2016-08-24 13:24:55,368 DEBUG: View 1 : 0.383886255924
+2016-08-24 13:24:55,509 DEBUG: View 2 : 0.568720379147
+2016-08-24 13:24:55,520 DEBUG: View 3 : 0.620853080569
+2016-08-24 13:24:56,581 DEBUG: Best view : Methyl_
+2016-08-24 13:25:25,491 DEBUG: Start: Iteration 354
+2016-08-24 13:25:25,512 DEBUG: View 0 : 0.687203791469
+2016-08-24 13:25:25,522 DEBUG: View 1 : 0.592417061611
+2016-08-24 13:25:25,677 DEBUG: View 2 : 0.601895734597
+2016-08-24 13:25:25,690 DEBUG: View 3 : 0.587677725118
+2016-08-24 13:25:26,866 DEBUG: Best view : Methyl_
+2016-08-24 13:25:55,868 DEBUG: Start: Iteration 355
+2016-08-24 13:25:55,889 DEBUG: View 0 : 0.450236966825
+2016-08-24 13:25:55,899 DEBUG: View 1 : 0.597156398104
+2016-08-24 13:25:56,036 DEBUG: View 2 : 0.549763033175
+2016-08-24 13:25:56,048 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:25:57,138 DEBUG: Best view : Clinic_
+2016-08-24 13:26:26,039 DEBUG: Start: Iteration 356
+2016-08-24 13:26:26,060 DEBUG: View 0 : 0.535545023697
+2016-08-24 13:26:26,070 DEBUG: View 1 : 0.625592417062
+2016-08-24 13:26:26,209 DEBUG: View 2 : 0.502369668246
+2016-08-24 13:26:26,220 DEBUG: View 3 : 0.630331753555
+2016-08-24 13:26:27,295 DEBUG: Best view : Clinic_
+2016-08-24 13:26:56,537 DEBUG: Start: Iteration 357
+2016-08-24 13:26:56,559 DEBUG: View 0 : 0.521327014218
+2016-08-24 13:26:56,568 DEBUG: View 1 : 0.758293838863
+2016-08-24 13:26:56,704 DEBUG: View 2 : 0.635071090047
+2016-08-24 13:26:56,715 DEBUG: View 3 : 0.592417061611
+2016-08-24 13:26:57,821 DEBUG: Best view : MiRNA__
+2016-08-24 13:27:26,994 DEBUG: Start: Iteration 358
+2016-08-24 13:27:27,015 DEBUG: View 0 : 0.630331753555
+2016-08-24 13:27:27,025 DEBUG: View 1 : 0.616113744076
+2016-08-24 13:27:27,162 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:27:27,174 DEBUG: View 3 : 0.554502369668
+2016-08-24 13:27:28,247 DEBUG: Best view : Methyl_
+2016-08-24 13:27:58,044 DEBUG: Start: Iteration 359
+2016-08-24 13:27:58,064 DEBUG: View 0 : 0.545023696682
+2016-08-24 13:27:58,074 DEBUG: View 1 : 0.469194312796
+2016-08-24 13:27:58,197 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:27:58,209 DEBUG: View 3 : 0.616113744076
+2016-08-24 13:27:59,367 DEBUG: Best view : Clinic_
+2016-08-24 13:28:28,618 DEBUG: Start: Iteration 360
+2016-08-24 13:28:28,639 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:28:28,650 DEBUG: View 1 : 0.379146919431
+2016-08-24 13:28:28,788 DEBUG: View 2 : 0.587677725118
+2016-08-24 13:28:28,800 DEBUG: View 3 : 0.625592417062
+2016-08-24 13:28:30,145 DEBUG: Best view : Clinic_
+2016-08-24 13:28:59,484 DEBUG: Start: Iteration 361
+2016-08-24 13:28:59,505 DEBUG: View 0 : 0.57345971564
+2016-08-24 13:28:59,515 DEBUG: View 1 : 0.620853080569
+2016-08-24 13:28:59,644 DEBUG: View 2 : 0.592417061611
+2016-08-24 13:28:59,655 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:29:00,763 DEBUG: Best view : MiRNA__
+2016-08-24 13:29:30,434 DEBUG: Start: Iteration 362
+2016-08-24 13:29:30,455 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:29:30,465 DEBUG: View 1 : 0.45971563981
+2016-08-24 13:29:30,598 DEBUG: View 2 : 0.554502369668
+2016-08-24 13:29:30,610 DEBUG: View 3 : 0.592417061611
+2016-08-24 13:29:31,731 DEBUG: Best view : Clinic_
+2016-08-24 13:30:01,786 DEBUG: Start: Iteration 363
+2016-08-24 13:30:01,807 DEBUG: View 0 : 0.630331753555
+2016-08-24 13:30:01,816 DEBUG: View 1 : 0.502369668246
+2016-08-24 13:30:01,953 DEBUG: View 2 : 0.60663507109
+2016-08-24 13:30:01,964 DEBUG: View 3 : 0.507109004739
+2016-08-24 13:30:03,086 DEBUG: Best view : Methyl_
+2016-08-24 13:30:32,971 DEBUG: Start: Iteration 364
+2016-08-24 13:30:32,993 DEBUG: View 0 : 0.554502369668
+2016-08-24 13:30:33,003 DEBUG: View 1 : 0.644549763033
+2016-08-24 13:30:33,126 DEBUG: View 2 : 0.592417061611
+2016-08-24 13:30:33,137 DEBUG: View 3 : 0.616113744076
+2016-08-24 13:30:34,239 DEBUG: Best view : Clinic_
+2016-08-24 13:31:04,052 DEBUG: Start: Iteration 365
+2016-08-24 13:31:04,072 DEBUG: View 0 : 0.545023696682
+2016-08-24 13:31:04,082 DEBUG: View 1 : 0.706161137441
+2016-08-24 13:31:04,215 DEBUG: View 2 : 0.492890995261
+2016-08-24 13:31:04,226 DEBUG: View 3 : 0.554502369668
+2016-08-24 13:31:05,331 DEBUG: Best view : MiRNA__
+2016-08-24 13:31:35,076 DEBUG: Start: Iteration 366
+2016-08-24 13:31:35,096 DEBUG: View 0 : 0.658767772512
+2016-08-24 13:31:35,106 DEBUG: View 1 : 0.54028436019
+2016-08-24 13:31:35,242 DEBUG: View 2 : 0.554502369668
+2016-08-24 13:31:35,253 DEBUG: View 3 : 0.587677725118
+2016-08-24 13:31:36,362 DEBUG: Best view : Methyl_
+2016-08-24 13:32:05,866 DEBUG: Start: Iteration 367
+2016-08-24 13:32:05,887 DEBUG: View 0 : 0.630331753555
+2016-08-24 13:32:05,897 DEBUG: View 1 : 0.677725118483
+2016-08-24 13:32:06,019 DEBUG: View 2 : 0.587677725118
+2016-08-24 13:32:06,030 DEBUG: View 3 : 0.592417061611
+2016-08-24 13:32:07,151 DEBUG: Best view : MiRNA__
+2016-08-24 13:32:37,659 DEBUG: Start: Iteration 368
+2016-08-24 13:32:37,680 DEBUG: View 0 : 0.625592417062
+2016-08-24 13:32:37,691 DEBUG: View 1 : 0.563981042654
+2016-08-24 13:32:37,812 DEBUG: View 2 : 0.511848341232
+2016-08-24 13:32:37,822 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:32:38,995 DEBUG: Best view : Methyl_
+2016-08-24 13:33:09,312 DEBUG: Start: Iteration 369
+2016-08-24 13:33:09,334 DEBUG: View 0 : 0.464454976303
+2016-08-24 13:33:09,348 DEBUG: View 1 : 0.549763033175
+2016-08-24 13:33:09,482 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:33:09,498 DEBUG: View 3 : 0.625592417062
+2016-08-24 13:33:10,676 DEBUG: Best view : Clinic_
+2016-08-24 13:33:40,714 DEBUG: Start: Iteration 370
+2016-08-24 13:33:40,736 DEBUG: View 0 : 0.507109004739
+2016-08-24 13:33:40,745 DEBUG: View 1 : 0.644549763033
+2016-08-24 13:33:40,862 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:33:40,872 DEBUG: View 3 : 0.611374407583
+2016-08-24 13:33:41,996 DEBUG: Best view : Clinic_
+2016-08-24 13:34:11,589 DEBUG: Start: Iteration 371
+2016-08-24 13:34:11,611 DEBUG: View 0 : 0.516587677725
+2016-08-24 13:34:11,620 DEBUG: View 1 : 0.450236966825
+2016-08-24 13:34:11,740 DEBUG: View 2 : 0.597156398104
+2016-08-24 13:34:11,749 DEBUG: View 3 : 0.582938388626
+2016-08-24 13:34:12,914 DEBUG: Best view : Clinic_
+2016-08-24 13:34:42,966 DEBUG: Start: Iteration 372
+2016-08-24 13:34:42,987 DEBUG: View 0 : 0.54028436019
+2016-08-24 13:34:42,997 DEBUG: View 1 : 0.597156398104
+2016-08-24 13:34:43,125 DEBUG: View 2 : 0.620853080569
+2016-08-24 13:34:43,134 DEBUG: View 3 : 0.611374407583
+2016-08-24 13:34:44,307 DEBUG: Best view : RANSeq_
+2016-08-24 13:35:14,647 DEBUG: Start: Iteration 373
+2016-08-24 13:35:14,668 DEBUG: View 0 : 0.654028436019
+2016-08-24 13:35:14,680 DEBUG: View 1 : 0.421800947867
+2016-08-24 13:35:14,805 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:35:14,814 DEBUG: View 3 : 0.578199052133
+2016-08-24 13:35:15,960 DEBUG: Best view : Methyl_
+2016-08-24 13:35:46,317 DEBUG: Start: Iteration 374
+2016-08-24 13:35:46,339 DEBUG: View 0 : 0.492890995261
+2016-08-24 13:35:46,349 DEBUG: View 1 : 0.625592417062
+2016-08-24 13:35:46,466 DEBUG: View 2 : 0.535545023697
+2016-08-24 13:35:46,475 DEBUG: View 3 : 0.511848341232
+2016-08-24 13:35:47,650 DEBUG: Best view : MiRNA__
+2016-08-24 13:36:17,996 DEBUG: Start: Iteration 375
+2016-08-24 13:36:18,018 DEBUG: View 0 : 0.587677725118
+2016-08-24 13:36:18,028 DEBUG: View 1 : 0.388625592417
+2016-08-24 13:36:18,170 DEBUG: View 2 : 0.563981042654
+2016-08-24 13:36:18,181 DEBUG: View 3 : 0.630331753555
+2016-08-24 13:36:19,343 DEBUG: Best view : Clinic_
+2016-08-24 13:36:49,753 DEBUG: Start: Iteration 376
+2016-08-24 13:36:49,774 DEBUG: View 0 : 0.445497630332
+2016-08-24 13:36:49,784 DEBUG: View 1 : 0.616113744076
+2016-08-24 13:36:49,904 DEBUG: View 2 : 0.554502369668
+2016-08-24 13:36:49,913 DEBUG: View 3 : 0.597156398104
+2016-08-24 13:36:51,145 DEBUG: Best view : Clinic_
+2016-08-24 13:37:21,399 DEBUG: Start: Iteration 377
+2016-08-24 13:37:21,420 DEBUG: View 0 : 0.545023696682
+2016-08-24 13:37:21,430 DEBUG: View 1 : 0.611374407583
+2016-08-24 13:37:21,550 DEBUG: View 2 : 0.502369668246
+2016-08-24 13:37:21,560 DEBUG: View 3 : 0.521327014218
+2016-08-24 13:37:22,689 DEBUG: Best view : MiRNA__
+2016-08-24 13:37:52,749 DEBUG: Start: Iteration 378
+2016-08-24 13:37:52,770 DEBUG: View 0 : 0.42654028436
+2016-08-24 13:37:52,779 DEBUG: View 1 : 0.587677725118
+2016-08-24 13:37:52,902 DEBUG: View 2 : 0.582938388626
+2016-08-24 13:37:52,912 DEBUG: View 3 : 0.620853080569
+2016-08-24 13:37:54,077 DEBUG: Best view : Clinic_
+2016-08-24 13:38:24,175 DEBUG: Start: Iteration 379
+2016-08-24 13:38:24,197 DEBUG: View 0 : 0.625592417062
+2016-08-24 13:38:24,206 DEBUG: View 1 : 0.75355450237
+2016-08-24 13:38:24,329 DEBUG: View 2 : 0.526066350711
+2016-08-24 13:38:24,338 DEBUG: View 3 : 0.620853080569
+2016-08-24 13:38:25,566 DEBUG: Best view : MiRNA__
+2016-08-24 13:38:55,931 DEBUG: Start: Iteration 380
+2016-08-24 13:38:55,953 DEBUG: View 0 : 0.535545023697
+2016-08-24 13:38:55,962 DEBUG: View 1 : 0.677725118483
+2016-08-24 13:38:56,079 DEBUG: View 2 : 0.635071090047
+2016-08-24 13:38:56,088 DEBUG: View 3 : 0.616113744076
+2016-08-24 13:38:57,256 DEBUG: Best view : MiRNA__
+2016-08-24 13:39:27,647 DEBUG: Start: Iteration 381
+2016-08-24 13:39:27,668 DEBUG: View 0 : 0.473933649289
+2016-08-24 13:39:27,678 DEBUG: View 1 : 0.620853080569
+2016-08-24 13:39:27,798 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:39:27,808 DEBUG: View 3 : 0.616113744076
+2016-08-24 13:39:28,946 DEBUG: Best view : Clinic_
+2016-08-24 13:40:00,455 DEBUG: Start: Iteration 382
+2016-08-24 13:40:00,481 DEBUG: View 0 : 0.42654028436
+2016-08-24 13:40:00,492 DEBUG: View 1 : 0.436018957346
+2016-08-24 13:40:00,631 DEBUG: View 2 : 0.635071090047
+2016-08-24 13:40:00,643 DEBUG: View 3 : 0.616113744076
+2016-08-24 13:40:01,991 DEBUG: Best view : RANSeq_
+2016-08-24 13:40:32,518 DEBUG: Start: Iteration 383
+2016-08-24 13:40:32,539 DEBUG: View 0 : 0.436018957346
+2016-08-24 13:40:32,548 DEBUG: View 1 : 0.60663507109
+2016-08-24 13:40:32,668 DEBUG: View 2 : 0.507109004739
+2016-08-24 13:40:32,678 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:40:33,824 DEBUG: Best view : Clinic_
+2016-08-24 13:41:04,952 DEBUG: Start: Iteration 384
+2016-08-24 13:41:04,974 DEBUG: View 0 : 0.587677725118
+2016-08-24 13:41:04,983 DEBUG: View 1 : 0.597156398104
+2016-08-24 13:41:05,103 DEBUG: View 2 : 0.597156398104
+2016-08-24 13:41:05,112 DEBUG: View 3 : 0.545023696682
+2016-08-24 13:41:06,291 DEBUG: Best view : MiRNA__
+2016-08-24 13:41:37,036 DEBUG: Start: Iteration 385
+2016-08-24 13:41:37,056 DEBUG: View 0 : 0.530805687204
+2016-08-24 13:41:37,066 DEBUG: View 1 : 0.630331753555
+2016-08-24 13:41:37,181 DEBUG: View 2 : 0.535545023697
+2016-08-24 13:41:37,191 DEBUG: View 3 : 0.582938388626
+2016-08-24 13:41:38,358 DEBUG: Best view : MiRNA__
+2016-08-24 13:42:09,865 DEBUG: Start: Iteration 386
+2016-08-24 13:42:09,889 DEBUG: View 0 : 0.635071090047
+2016-08-24 13:42:09,902 DEBUG: View 1 : 0.582938388626
+2016-08-24 13:42:10,037 DEBUG: View 2 : 0.57345971564
+2016-08-24 13:42:10,046 DEBUG: View 3 : 0.663507109005
+2016-08-24 13:42:11,381 DEBUG: Best view : Clinic_
+2016-08-24 13:42:43,246 DEBUG: Start: Iteration 387
+2016-08-24 13:42:43,270 DEBUG: View 0 : 0.530805687204
+2016-08-24 13:42:43,281 DEBUG: View 1 : 0.497630331754
+2016-08-24 13:42:43,425 DEBUG: View 2 : 0.554502369668
+2016-08-24 13:42:43,436 DEBUG: View 3 : 0.663507109005
+2016-08-24 13:42:44,706 DEBUG: Best view : Clinic_
+2016-08-24 13:43:15,848 DEBUG: Start: Iteration 388
+2016-08-24 13:43:15,869 DEBUG: View 0 : 0.54028436019
+2016-08-24 13:43:15,879 DEBUG: View 1 : 0.654028436019
+2016-08-24 13:43:15,990 DEBUG: View 2 : 0.568720379147
+2016-08-24 13:43:15,999 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:43:17,163 DEBUG: Best view : MiRNA__
+2016-08-24 13:43:48,364 DEBUG: Start: Iteration 389
+2016-08-24 13:43:48,385 DEBUG: View 0 : 0.635071090047
+2016-08-24 13:43:48,394 DEBUG: View 1 : 0.687203791469
+2016-08-24 13:43:48,501 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:43:48,510 DEBUG: View 3 : 0.625592417062
+2016-08-24 13:43:49,674 DEBUG: Best view : MiRNA__
+2016-08-24 13:44:21,139 DEBUG: Start: Iteration 390
+2016-08-24 13:44:21,160 DEBUG: View 0 : 0.492890995261
+2016-08-24 13:44:21,170 DEBUG: View 1 : 0.45971563981
+2016-08-24 13:44:21,292 DEBUG: View 2 : 0.502369668246
+2016-08-24 13:44:21,301 DEBUG: View 3 : 0.563981042654
+2016-08-24 13:44:22,530 DEBUG: Best view : Clinic_
+2016-08-24 13:44:54,159 DEBUG: Start: Iteration 391
+2016-08-24 13:44:54,180 DEBUG: View 0 : 0.497630331754
+2016-08-24 13:44:54,190 DEBUG: View 1 : 0.483412322275
+2016-08-24 13:44:54,307 DEBUG: View 2 : 0.582938388626
+2016-08-24 13:44:54,318 DEBUG: View 3 : 0.554502369668
+2016-08-24 13:44:55,517 DEBUG: Best view : RANSeq_
+2016-08-24 13:45:27,112 DEBUG: Start: Iteration 392
+2016-08-24 13:45:27,133 DEBUG: View 0 : 0.473933649289
+2016-08-24 13:45:27,143 DEBUG: View 1 : 0.601895734597
+2016-08-24 13:45:27,260 DEBUG: View 2 : 0.601895734597
+2016-08-24 13:45:27,270 DEBUG: View 3 : 0.635071090047
+2016-08-24 13:45:28,443 DEBUG: Best view : Clinic_
+2016-08-24 13:46:00,019 DEBUG: Start: Iteration 393
+2016-08-24 13:46:00,040 DEBUG: View 0 : 0.691943127962
+2016-08-24 13:46:00,050 DEBUG: View 1 : 0.421800947867
+2016-08-24 13:46:00,166 DEBUG: View 2 : 0.521327014218
+2016-08-24 13:46:00,175 DEBUG: View 3 : 0.559241706161
+2016-08-24 13:46:01,367 DEBUG: Best view : Methyl_
+2016-08-24 13:46:33,081 DEBUG: Start: Iteration 394
+2016-08-24 13:46:33,102 DEBUG: View 0 : 0.549763033175
+2016-08-24 13:46:33,111 DEBUG: View 1 : 0.545023696682
+2016-08-24 13:46:33,231 DEBUG: View 2 : 0.592417061611
+2016-08-24 13:46:33,240 DEBUG: View 3 : 0.635071090047
+2016-08-24 13:46:34,419 DEBUG: Best view : Clinic_
+2016-08-24 13:47:06,196 DEBUG: Start: Iteration 395
+2016-08-24 13:47:06,221 DEBUG: View 0 : 0.464454976303
+2016-08-24 13:47:06,232 DEBUG: View 1 : 0.597156398104
+2016-08-24 13:47:06,363 DEBUG: View 2 : 0.578199052133
+2016-08-24 13:47:06,372 DEBUG: View 3 : 0.578199052133
+2016-08-24 13:47:07,572 DEBUG: Best view : Clinic_
+2016-08-24 13:47:39,732 DEBUG: Start: Iteration 396
+2016-08-24 13:47:39,754 DEBUG: View 0 : 0.582938388626
+2016-08-24 13:47:39,764 DEBUG: View 1 : 0.658767772512
+2016-08-24 13:47:39,911 DEBUG: View 2 : 0.554502369668
+2016-08-24 13:47:39,920 DEBUG: View 3 : 0.545023696682
+2016-08-24 13:47:41,213 DEBUG: Best view : MiRNA__
+2016-08-24 13:48:13,299 DEBUG: Start: Iteration 397
+2016-08-24 13:48:13,320 DEBUG: View 0 : 0.635071090047
+2016-08-24 13:48:13,330 DEBUG: View 1 : 0.644549763033
+2016-08-24 13:48:13,453 DEBUG: View 2 : 0.611374407583
+2016-08-24 13:48:13,463 DEBUG: View 3 : 0.654028436019
+2016-08-24 13:48:14,683 DEBUG: Best view : Clinic_
+2016-08-24 13:48:47,260 DEBUG: Start: Iteration 398
+2016-08-24 13:48:47,281 DEBUG: View 0 : 0.54028436019
+2016-08-24 13:48:47,290 DEBUG: View 1 : 0.625592417062
+2016-08-24 13:48:47,425 DEBUG: View 2 : 0.535545023697
+2016-08-24 13:48:47,435 DEBUG: View 3 : 0.545023696682
+2016-08-24 13:48:48,673 DEBUG: Best view : MiRNA__
+2016-08-24 13:49:20,843 DEBUG: Start: Iteration 399
+2016-08-24 13:49:20,864 DEBUG: View 0 : 0.829383886256
+2016-08-24 13:49:20,874 DEBUG: View 1 : 0.744075829384
+2016-08-24 13:49:20,991 DEBUG: View 2 : 0.597156398104
+2016-08-24 13:49:21,000 DEBUG: View 3 : 0.549763033175
+2016-08-24 13:49:22,365 DEBUG: Best view : Methyl_
+2016-08-24 13:49:55,510 DEBUG: Start: Iteration 400
+2016-08-24 13:49:55,537 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:49:55,548 DEBUG: View 1 : 0.649289099526
+2016-08-24 13:49:55,685 DEBUG: View 2 : 0.635071090047
+2016-08-24 13:49:55,695 DEBUG: View 3 : 0.691943127962
+2016-08-24 13:49:57,078 DEBUG: Best view : Clinic_
+2016-08-24 13:50:30,035 DEBUG: Start: Iteration 401
+2016-08-24 13:50:30,056 DEBUG: View 0 : 0.436018957346
+2016-08-24 13:50:30,065 DEBUG: View 1 : 0.677725118483
+2016-08-24 13:50:30,179 DEBUG: View 2 : 0.635071090047
+2016-08-24 13:50:30,188 DEBUG: View 3 : 0.597156398104
+2016-08-24 13:50:31,383 DEBUG: Best view : MiRNA__
+2016-08-24 13:51:03,983 DEBUG: Start: Iteration 402
+2016-08-24 13:51:04,005 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:51:04,014 DEBUG: View 1 : 0.644549763033
+2016-08-24 13:51:04,129 DEBUG: View 2 : 0.597156398104
+2016-08-24 13:51:04,138 DEBUG: View 3 : 0.706161137441
+2016-08-24 13:51:05,329 DEBUG: Best view : Clinic_
+2016-08-24 13:51:37,241 DEBUG: Start: Iteration 403
+2016-08-24 13:51:37,263 DEBUG: View 0 : 0.549763033175
+2016-08-24 13:51:37,273 DEBUG: View 1 : 0.369668246445
+2016-08-24 13:51:37,388 DEBUG: View 2 : 0.592417061611
+2016-08-24 13:51:37,397 DEBUG: View 3 : 0.658767772512
+2016-08-24 13:51:38,606 DEBUG: Best view : Clinic_
+2016-08-24 13:52:11,139 DEBUG: Start: Iteration 404
+2016-08-24 13:52:11,160 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:52:11,169 DEBUG: View 1 : 0.559241706161
+2016-08-24 13:52:11,289 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:52:11,298 DEBUG: View 3 : 0.554502369668
+2016-08-24 13:52:12,508 DEBUG: Best view : Methyl_
+2016-08-24 13:52:44,577 DEBUG: Start: Iteration 405
+2016-08-24 13:52:44,598 DEBUG: View 0 : 0.620853080569
+2016-08-24 13:52:44,608 DEBUG: View 1 : 0.625592417062
+2016-08-24 13:52:44,723 DEBUG: View 2 : 0.492890995261
+2016-08-24 13:52:44,732 DEBUG: View 3 : 0.625592417062
+2016-08-24 13:52:45,935 DEBUG: Best view : Clinic_
+2016-08-24 13:53:19,104 DEBUG: Start: Iteration 406
+2016-08-24 13:53:19,125 DEBUG: View 0 : 0.535545023697
+2016-08-24 13:53:19,134 DEBUG: View 1 : 0.625592417062
+2016-08-24 13:53:19,257 DEBUG: View 2 : 0.601895734597
+2016-08-24 13:53:19,266 DEBUG: View 3 : 0.658767772512
+2016-08-24 13:53:20,642 DEBUG: Best view : Clinic_
+2016-08-24 13:53:53,732 DEBUG: Start: Iteration 407
+2016-08-24 13:53:53,754 DEBUG: View 0 : 0.810426540284
+2016-08-24 13:53:53,764 DEBUG: View 1 : 0.341232227488
+2016-08-24 13:53:53,883 DEBUG: View 2 : 0.601895734597
+2016-08-24 13:53:53,892 DEBUG: View 3 : 0.611374407583
+2016-08-24 13:53:55,101 DEBUG: Best view : Methyl_
+2016-08-24 13:54:27,648 DEBUG: Start: Iteration 408
+2016-08-24 13:54:27,669 DEBUG: View 0 : 0.507109004739
+2016-08-24 13:54:27,679 DEBUG: View 1 : 0.464454976303
+2016-08-24 13:54:27,798 DEBUG: View 2 : 0.526066350711
+2016-08-24 13:54:27,807 DEBUG: View 3 : 0.436018957346
+2016-08-24 13:54:29,031 DEBUG: Best view : RANSeq_
+2016-08-24 13:55:02,477 DEBUG: Start: Iteration 409
+2016-08-24 13:55:02,498 DEBUG: View 0 : 0.663507109005
+2016-08-24 13:55:02,508 DEBUG: View 1 : 0.417061611374
+2016-08-24 13:55:02,624 DEBUG: View 2 : 0.63981042654
+2016-08-24 13:55:02,633 DEBUG: View 3 : 0.597156398104
+2016-08-24 13:55:03,877 DEBUG: Best view : Methyl_
+2016-08-24 13:55:37,510 DEBUG: Start: Iteration 410
+2016-08-24 13:55:37,531 DEBUG: View 0 : 0.658767772512
+2016-08-24 13:55:37,541 DEBUG: View 1 : 0.630331753555
+2016-08-24 13:55:37,664 DEBUG: View 2 : 0.620853080569
+2016-08-24 13:55:37,673 DEBUG: View 3 : 0.545023696682
+2016-08-24 13:55:38,897 DEBUG: Best view : Methyl_
+2016-08-24 13:56:12,501 DEBUG: Start: Iteration 411
+2016-08-24 13:56:12,523 DEBUG: View 0 : 0.635071090047
+2016-08-24 13:56:12,533 DEBUG: View 1 : 0.644549763033
+2016-08-24 13:56:12,666 DEBUG: View 2 : 0.516587677725
+2016-08-24 13:56:12,677 DEBUG: View 3 : 0.663507109005
+2016-08-24 13:56:13,983 DEBUG: Best view : Clinic_
+2016-08-24 13:56:47,750 DEBUG: Start: Iteration 412
+2016-08-24 13:56:47,771 DEBUG: View 0 : 0.502369668246
+2016-08-24 13:56:47,781 DEBUG: View 1 : 0.57345971564
+2016-08-24 13:56:47,892 DEBUG: View 2 : 0.63981042654
+2016-08-24 13:56:47,901 DEBUG: View 3 : 0.630331753555
+2016-08-24 13:56:49,135 DEBUG: Best view : Clinic_
+2016-08-24 13:57:23,645 DEBUG: Start: Iteration 413
+2016-08-24 13:57:23,666 DEBUG: View 0 : 0.488151658768
+2016-08-24 13:57:23,677 DEBUG: View 1 : 0.663507109005
+2016-08-24 13:57:23,802 DEBUG: View 2 : 0.582938388626
+2016-08-24 13:57:23,811 DEBUG: View 3 : 0.568720379147
+2016-08-24 13:57:25,057 DEBUG: Best view : MiRNA__
+2016-08-24 13:57:59,361 DEBUG: Start: Iteration 414
+2016-08-24 13:57:59,382 DEBUG: View 0 : 0.644549763033
+2016-08-24 13:57:59,391 DEBUG: View 1 : 0.63981042654
+2016-08-24 13:57:59,507 DEBUG: View 2 : 0.559241706161
+2016-08-24 13:57:59,516 DEBUG: View 3 : 0.582938388626
+2016-08-24 13:58:00,773 DEBUG: Best view : Methyl_
+2016-08-24 13:58:34,062 DEBUG: Start: Iteration 415
+2016-08-24 13:58:34,083 DEBUG: View 0 : 0.511848341232
+2016-08-24 13:58:34,093 DEBUG: View 1 : 0.597156398104
+2016-08-24 13:58:34,220 DEBUG: View 2 : 0.549763033175
+2016-08-24 13:58:34,229 DEBUG: View 3 : 0.554502369668
+2016-08-24 13:58:35,453 DEBUG: Best view : MiRNA__
+2016-08-24 13:59:08,331 DEBUG: Start: Iteration 416
+2016-08-24 13:59:08,352 DEBUG: View 0 : 0.54028436019
+2016-08-24 13:59:08,362 DEBUG: View 1 : 0.601895734597
+2016-08-24 13:59:08,476 DEBUG: View 2 : 0.616113744076
+2016-08-24 13:59:08,485 DEBUG: View 3 : 0.578199052133
+2016-08-24 13:59:09,711 DEBUG: Best view : MiRNA__
+2016-08-24 13:59:43,368 DEBUG: Start: Iteration 417
+2016-08-24 13:59:43,389 DEBUG: View 0 : 0.454976303318
+2016-08-24 13:59:43,399 DEBUG: View 1 : 0.710900473934
+2016-08-24 13:59:43,519 DEBUG: View 2 : 0.568720379147
+2016-08-24 13:59:43,528 DEBUG: View 3 : 0.687203791469
+2016-08-24 13:59:44,841 DEBUG: Best view : MiRNA__
+2016-08-24 14:00:18,976 DEBUG: Start: Iteration 418
+2016-08-24 14:00:18,997 DEBUG: View 0 : 0.658767772512
+2016-08-24 14:00:19,008 DEBUG: View 1 : 0.578199052133
+2016-08-24 14:00:19,124 DEBUG: View 2 : 0.592417061611
+2016-08-24 14:00:19,133 DEBUG: View 3 : 0.545023696682
+2016-08-24 14:00:20,396 DEBUG: Best view : Methyl_
+2016-08-24 14:00:54,344 DEBUG: Start: Iteration 419
+2016-08-24 14:00:54,365 DEBUG: View 0 : 0.516587677725
+2016-08-24 14:00:54,375 DEBUG: View 1 : 0.635071090047
+2016-08-24 14:00:54,498 DEBUG: View 2 : 0.568720379147
+2016-08-24 14:00:54,507 DEBUG: View 3 : 0.57345971564
+2016-08-24 14:00:55,752 DEBUG: Best view : MiRNA__
+2016-08-24 14:01:30,338 DEBUG: Start: Iteration 420
+2016-08-24 14:01:30,359 DEBUG: View 0 : 0.592417061611
+2016-08-24 14:01:30,369 DEBUG: View 1 : 0.677725118483
+2016-08-24 14:01:30,504 DEBUG: View 2 : 0.554502369668
+2016-08-24 14:01:30,514 DEBUG: View 3 : 0.60663507109
+2016-08-24 14:01:31,799 DEBUG: Best view : MiRNA__
+2016-08-24 14:02:05,514 DEBUG: Start: Iteration 421
+2016-08-24 14:02:05,535 DEBUG: View 0 : 0.545023696682
+2016-08-24 14:02:05,545 DEBUG: View 1 : 0.777251184834
+2016-08-24 14:02:05,681 DEBUG: View 2 : 0.597156398104
+2016-08-24 14:02:05,691 DEBUG: View 3 : 0.635071090047
+2016-08-24 14:02:06,975 DEBUG: Best view : MiRNA__
+2016-08-24 14:02:40,836 DEBUG: Start: Iteration 422
+2016-08-24 14:02:40,857 DEBUG: View 0 : 0.597156398104
+2016-08-24 14:02:40,867 DEBUG: View 1 : 0.672985781991
+2016-08-24 14:02:40,989 DEBUG: View 2 : 0.554502369668
+2016-08-24 14:02:40,998 DEBUG: View 3 : 0.616113744076
+2016-08-24 14:02:42,282 DEBUG: Best view : MiRNA__
+2016-08-24 14:03:16,292 DEBUG: Start: Iteration 423
+2016-08-24 14:03:16,313 DEBUG: View 0 : 0.507109004739
+2016-08-24 14:03:16,322 DEBUG: View 1 : 0.497630331754
+2016-08-24 14:03:16,440 DEBUG: View 2 : 0.507109004739
+2016-08-24 14:03:16,449 DEBUG: View 3 : 0.620853080569
+2016-08-24 14:03:17,705 DEBUG: Best view : Clinic_
+2016-08-24 14:03:52,074 DEBUG: Start: Iteration 424
+2016-08-24 14:03:52,095 DEBUG: View 0 : 0.601895734597
+2016-08-24 14:03:52,104 DEBUG: View 1 : 0.616113744076
+2016-08-24 14:03:52,220 DEBUG: View 2 : 0.597156398104
+2016-08-24 14:03:52,229 DEBUG: View 3 : 0.497630331754
+2016-08-24 14:03:53,482 DEBUG: Best view : RANSeq_
+2016-08-24 14:04:27,383 DEBUG: Start: Iteration 425
+2016-08-24 14:04:27,404 DEBUG: View 0 : 0.454976303318
+2016-08-24 14:04:27,414 DEBUG: View 1 : 0.644549763033
+2016-08-24 14:04:27,534 DEBUG: View 2 : 0.563981042654
+2016-08-24 14:04:27,543 DEBUG: View 3 : 0.497630331754
+2016-08-24 14:04:28,823 DEBUG: Best view : MiRNA__
+2016-08-24 14:05:03,346 DEBUG: Start: Iteration 426
+2016-08-24 14:05:03,367 DEBUG: View 0 : 0.492890995261
+2016-08-24 14:05:03,377 DEBUG: View 1 : 0.549763033175
+2016-08-24 14:05:03,497 DEBUG: View 2 : 0.535545023697
+2016-08-24 14:05:03,506 DEBUG: View 3 : 0.469194312796
+2016-08-24 14:05:04,788 DEBUG: Best view : MiRNA__
+2016-08-24 14:05:39,257 DEBUG: Start: Iteration 427
+2016-08-24 14:05:39,279 DEBUG: View 0 : 0.620853080569
+2016-08-24 14:05:39,288 DEBUG: View 1 : 0.469194312796
+2016-08-24 14:05:39,410 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:05:39,419 DEBUG: View 3 : 0.568720379147
+2016-08-24 14:05:40,675 DEBUG: Best view : Methyl_
+2016-08-24 14:06:14,724 DEBUG: Start: Iteration 428
+2016-08-24 14:06:14,745 DEBUG: View 0 : 0.582938388626
+2016-08-24 14:06:14,755 DEBUG: View 1 : 0.654028436019
+2016-08-24 14:06:14,913 DEBUG: View 2 : 0.530805687204
+2016-08-24 14:06:14,927 DEBUG: View 3 : 0.668246445498
+2016-08-24 14:06:16,235 DEBUG: Best view : Clinic_
+2016-08-24 14:06:50,711 DEBUG: Start: Iteration 429
+2016-08-24 14:06:50,731 DEBUG: View 0 : 0.611374407583
+2016-08-24 14:06:50,741 DEBUG: View 1 : 0.649289099526
+2016-08-24 14:06:50,867 DEBUG: View 2 : 0.611374407583
+2016-08-24 14:06:50,879 DEBUG: View 3 : 0.625592417062
+2016-08-24 14:06:52,142 DEBUG: Best view : Clinic_
+2016-08-24 14:07:25,955 DEBUG: Start: Iteration 430
+2016-08-24 14:07:25,977 DEBUG: View 0 : 0.488151658768
+2016-08-24 14:07:25,986 DEBUG: View 1 : 0.663507109005
+2016-08-24 14:07:26,117 DEBUG: View 2 : 0.521327014218
+2016-08-24 14:07:26,129 DEBUG: View 3 : 0.440758293839
+2016-08-24 14:07:27,392 DEBUG: Best view : MiRNA__
+2016-08-24 14:08:01,799 DEBUG: Start: Iteration 431
+2016-08-24 14:08:01,820 DEBUG: View 0 : 0.644549763033
+2016-08-24 14:08:01,830 DEBUG: View 1 : 0.63981042654
+2016-08-24 14:08:01,953 DEBUG: View 2 : 0.563981042654
+2016-08-24 14:08:01,965 DEBUG: View 3 : 0.526066350711
+2016-08-24 14:08:03,237 DEBUG: Best view : Methyl_
+2016-08-24 14:08:37,425 DEBUG: Start: Iteration 432
+2016-08-24 14:08:37,446 DEBUG: View 0 : 0.511848341232
+2016-08-24 14:08:37,455 DEBUG: View 1 : 0.649289099526
+2016-08-24 14:08:37,583 DEBUG: View 2 : 0.502369668246
+2016-08-24 14:08:37,594 DEBUG: View 3 : 0.654028436019
+2016-08-24 14:08:38,862 DEBUG: Best view : Clinic_
+2016-08-24 14:09:13,162 DEBUG: Start: Iteration 433
+2016-08-24 14:09:13,183 DEBUG: View 0 : 0.57345971564
+2016-08-24 14:09:13,192 DEBUG: View 1 : 0.454976303318
+2016-08-24 14:09:13,326 DEBUG: View 2 : 0.60663507109
+2016-08-24 14:09:13,338 DEBUG: View 3 : 0.696682464455
+2016-08-24 14:09:14,619 DEBUG: Best view : Clinic_
+2016-08-24 14:09:50,222 DEBUG: Start: Iteration 434
+2016-08-24 14:09:50,243 DEBUG: View 0 : 0.473933649289
+2016-08-24 14:09:50,253 DEBUG: View 1 : 0.469194312796
+2016-08-24 14:09:50,388 DEBUG: View 2 : 0.611374407583
+2016-08-24 14:09:50,399 DEBUG: View 3 : 0.473933649289
+2016-08-24 14:09:51,683 DEBUG: Best view : RANSeq_
+2016-08-24 14:10:26,874 DEBUG: Start: Iteration 435
+2016-08-24 14:10:26,896 DEBUG: View 0 : 0.464454976303
+2016-08-24 14:10:26,906 DEBUG: View 1 : 0.616113744076
+2016-08-24 14:10:27,058 DEBUG: View 2 : 0.554502369668
+2016-08-24 14:10:27,068 DEBUG: View 3 : 0.691943127962
+2016-08-24 14:10:28,544 DEBUG: Best view : Clinic_
+2016-08-24 14:11:04,720 DEBUG: Start: Iteration 436
+2016-08-24 14:11:04,741 DEBUG: View 0 : 0.417061611374
+2016-08-24 14:11:04,750 DEBUG: View 1 : 0.635071090047
+2016-08-24 14:11:04,869 DEBUG: View 2 : 0.464454976303
+2016-08-24 14:11:04,879 DEBUG: View 3 : 0.654028436019
+2016-08-24 14:11:06,172 DEBUG: Best view : MiRNA__
+2016-08-24 14:11:40,928 DEBUG: Start: Iteration 437
+2016-08-24 14:11:40,949 DEBUG: View 0 : 0.625592417062
+2016-08-24 14:11:40,959 DEBUG: View 1 : 0.483412322275
+2016-08-24 14:11:41,090 DEBUG: View 2 : 0.488151658768
+2016-08-24 14:11:41,099 DEBUG: View 3 : 0.587677725118
+2016-08-24 14:11:42,392 DEBUG: Best view : Methyl_
+2016-08-24 14:12:17,624 DEBUG: Start: Iteration 438
+2016-08-24 14:12:17,645 DEBUG: View 0 : 0.431279620853
+2016-08-24 14:12:17,655 DEBUG: View 1 : 0.644549763033
+2016-08-24 14:12:17,781 DEBUG: View 2 : 0.620853080569
+2016-08-24 14:12:17,790 DEBUG: View 3 : 0.507109004739
+2016-08-24 14:12:19,346 DEBUG: Best view : RANSeq_
+2016-08-24 14:12:55,038 DEBUG: Start: Iteration 439
+2016-08-24 14:12:55,063 DEBUG: View 0 : 0.630331753555
+2016-08-24 14:12:55,073 DEBUG: View 1 : 0.611374407583
+2016-08-24 14:12:55,216 DEBUG: View 2 : 0.597156398104
+2016-08-24 14:12:55,225 DEBUG: View 3 : 0.635071090047
+2016-08-24 14:12:56,554 DEBUG: Best view : Clinic_
+2016-08-24 14:13:32,726 DEBUG: Start: Iteration 440
+2016-08-24 14:13:32,747 DEBUG: View 0 : 0.611374407583
+2016-08-24 14:13:32,758 DEBUG: View 1 : 0.587677725118
+2016-08-24 14:13:32,905 DEBUG: View 2 : 0.625592417062
+2016-08-24 14:13:32,916 DEBUG: View 3 : 0.57345971564
+2016-08-24 14:13:34,216 DEBUG: Best view : RANSeq_
+2016-08-24 14:14:09,458 DEBUG: Start: Iteration 441
+2016-08-24 14:14:09,479 DEBUG: View 0 : 0.563981042654
+2016-08-24 14:14:09,489 DEBUG: View 1 : 0.810426540284
+2016-08-24 14:14:09,624 DEBUG: View 2 : 0.578199052133
+2016-08-24 14:14:09,636 DEBUG: View 3 : 0.597156398104
+2016-08-24 14:14:10,973 DEBUG: Best view : MiRNA__
+2016-08-24 14:14:46,186 DEBUG: Start: Iteration 442
+2016-08-24 14:14:46,208 DEBUG: View 0 : 0.672985781991
+2016-08-24 14:14:46,218 DEBUG: View 1 : 0.464454976303
+2016-08-24 14:14:46,347 DEBUG: View 2 : 0.654028436019
+2016-08-24 14:14:46,358 DEBUG: View 3 : 0.57345971564
+2016-08-24 14:14:47,659 DEBUG: Best view : Methyl_
+2016-08-24 14:15:24,290 DEBUG: Start: Iteration 443
+2016-08-24 14:15:24,311 DEBUG: View 0 : 0.658767772512
+2016-08-24 14:15:24,321 DEBUG: View 1 : 0.658767772512
+2016-08-24 14:15:24,494 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:15:24,507 DEBUG: View 3 : 0.511848341232
+2016-08-24 14:15:25,989 DEBUG: Best view : Methyl_
+2016-08-24 14:16:02,481 DEBUG: Start: Iteration 444
+2016-08-24 14:16:02,502 DEBUG: View 0 : 0.568720379147
+2016-08-24 14:16:02,511 DEBUG: View 1 : 0.611374407583
+2016-08-24 14:16:02,641 DEBUG: View 2 : 0.630331753555
+2016-08-24 14:16:02,652 DEBUG: View 3 : 0.706161137441
+2016-08-24 14:16:04,126 DEBUG: Best view : Clinic_
+2016-08-24 14:16:40,930 DEBUG: Start: Iteration 445
+2016-08-24 14:16:40,951 DEBUG: View 0 : 0.625592417062
+2016-08-24 14:16:40,960 DEBUG: View 1 : 0.492890995261
+2016-08-24 14:16:41,091 DEBUG: View 2 : 0.54028436019
+2016-08-24 14:16:41,102 DEBUG: View 3 : 0.516587677725
+2016-08-24 14:16:42,421 DEBUG: Best view : Methyl_
+2016-08-24 14:17:18,422 DEBUG: Start: Iteration 446
+2016-08-24 14:17:18,444 DEBUG: View 0 : 0.478672985782
+2016-08-24 14:17:18,453 DEBUG: View 1 : 0.63981042654
+2016-08-24 14:17:18,602 DEBUG: View 2 : 0.60663507109
+2016-08-24 14:17:18,612 DEBUG: View 3 : 0.620853080569
+2016-08-24 14:17:20,117 DEBUG: Best view : Clinic_
+2016-08-24 14:17:57,426 DEBUG: Start: Iteration 447
+2016-08-24 14:17:57,450 DEBUG: View 0 : 0.469194312796
+2016-08-24 14:17:57,461 DEBUG: View 1 : 0.601895734597
+2016-08-24 14:17:57,600 DEBUG: View 2 : 0.597156398104
+2016-08-24 14:17:57,611 DEBUG: View 3 : 0.568720379147
+2016-08-24 14:17:59,029 DEBUG: Best view : RANSeq_
+2016-08-24 14:18:35,354 DEBUG: Start: Iteration 448
+2016-08-24 14:18:35,375 DEBUG: View 0 : 0.630331753555
+2016-08-24 14:18:35,385 DEBUG: View 1 : 0.507109004739
+2016-08-24 14:18:35,505 DEBUG: View 2 : 0.616113744076
+2016-08-24 14:18:35,514 DEBUG: View 3 : 0.649289099526
+2016-08-24 14:18:36,846 DEBUG: Best view : Clinic_
+2016-08-24 14:19:13,619 DEBUG: Start: Iteration 449
+2016-08-24 14:19:13,641 DEBUG: View 0 : 0.616113744076
+2016-08-24 14:19:13,651 DEBUG: View 1 : 0.554502369668
+2016-08-24 14:19:13,792 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:19:13,801 DEBUG: View 3 : 0.521327014218
+2016-08-24 14:19:15,250 DEBUG: Best view : Methyl_
+2016-08-24 14:19:52,835 DEBUG: Start: Iteration 450
+2016-08-24 14:19:52,856 DEBUG: View 0 : 0.454976303318
+2016-08-24 14:19:52,865 DEBUG: View 1 : 0.649289099526
+2016-08-24 14:19:53,007 DEBUG: View 2 : 0.57345971564
+2016-08-24 14:19:53,042 DEBUG: View 3 : 0.554502369668
+2016-08-24 14:19:54,465 DEBUG: Best view : MiRNA__
+2016-08-24 14:20:31,239 DEBUG: Start: Iteration 451
+2016-08-24 14:20:31,261 DEBUG: View 0 : 0.559241706161
+2016-08-24 14:20:31,271 DEBUG: View 1 : 0.473933649289
+2016-08-24 14:20:31,395 DEBUG: View 2 : 0.535545023697
+2016-08-24 14:20:31,407 DEBUG: View 3 : 0.658767772512
+2016-08-24 14:20:32,738 DEBUG: Best view : Clinic_
+2016-08-24 14:21:09,265 DEBUG: Start: Iteration 452
+2016-08-24 14:21:09,286 DEBUG: View 0 : 0.601895734597
+2016-08-24 14:21:09,296 DEBUG: View 1 : 0.582938388626
+2016-08-24 14:21:09,420 DEBUG: View 2 : 0.57345971564
+2016-08-24 14:21:09,432 DEBUG: View 3 : 0.644549763033
+2016-08-24 14:21:10,870 DEBUG: Best view : Clinic_
+2016-08-24 14:21:47,810 DEBUG: Start: Iteration 453
+2016-08-24 14:21:47,835 DEBUG: View 0 : 0.473933649289
+2016-08-24 14:21:47,852 DEBUG: View 1 : 0.578199052133
+2016-08-24 14:21:48,046 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:21:48,058 DEBUG: View 3 : 0.57345971564
+2016-08-24 14:21:49,470 DEBUG: Best view : Clinic_
+2016-08-24 14:22:26,194 DEBUG: Start: Iteration 454
+2016-08-24 14:22:26,214 DEBUG: View 0 : 0.492890995261
+2016-08-24 14:22:26,224 DEBUG: View 1 : 0.516587677725
+2016-08-24 14:22:26,352 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:22:26,363 DEBUG: View 3 : 0.535545023697
+2016-08-24 14:22:27,705 DEBUG: Best view : RANSeq_
+2016-08-24 14:23:05,443 DEBUG: Start: Iteration 455
+2016-08-24 14:23:05,468 DEBUG: View 0 : 0.445497630332
+2016-08-24 14:23:05,479 DEBUG: View 1 : 0.597156398104
+2016-08-24 14:23:05,630 DEBUG: View 2 : 0.611374407583
+2016-08-24 14:23:05,642 DEBUG: View 3 : 0.601895734597
+2016-08-24 14:23:06,986 DEBUG: Best view : RANSeq_
+2016-08-24 14:23:44,594 DEBUG: Start: Iteration 456
+2016-08-24 14:23:44,616 DEBUG: View 0 : 0.578199052133
+2016-08-24 14:23:44,626 DEBUG: View 1 : 0.57345971564
+2016-08-24 14:23:44,757 DEBUG: View 2 : 0.620853080569
+2016-08-24 14:23:44,768 DEBUG: View 3 : 0.559241706161
+2016-08-24 14:23:46,145 DEBUG: Best view : RANSeq_
+2016-08-24 14:24:23,164 DEBUG: Start: Iteration 457
+2016-08-24 14:24:23,185 DEBUG: View 0 : 0.554502369668
+2016-08-24 14:24:23,194 DEBUG: View 1 : 0.682464454976
+2016-08-24 14:24:23,314 DEBUG: View 2 : 0.578199052133
+2016-08-24 14:24:23,325 DEBUG: View 3 : 0.507109004739
+2016-08-24 14:24:24,700 DEBUG: Best view : MiRNA__
+2016-08-24 14:25:02,897 DEBUG: Start: Iteration 458
+2016-08-24 14:25:02,918 DEBUG: View 0 : 0.440758293839
+2016-08-24 14:25:02,928 DEBUG: View 1 : 0.483412322275
+2016-08-24 14:25:03,068 DEBUG: View 2 : 0.563981042654
+2016-08-24 14:25:03,077 DEBUG: View 3 : 0.587677725118
+2016-08-24 14:25:04,547 DEBUG: Best view : Clinic_
+2016-08-24 14:25:42,116 DEBUG: Start: Iteration 459
+2016-08-24 14:25:42,137 DEBUG: View 0 : 0.644549763033
+2016-08-24 14:25:42,147 DEBUG: View 1 : 0.54028436019
+2016-08-24 14:25:42,279 DEBUG: View 2 : 0.578199052133
+2016-08-24 14:25:42,289 DEBUG: View 3 : 0.535545023697
+2016-08-24 14:25:43,672 DEBUG: Best view : Methyl_
+2016-08-24 14:26:20,762 DEBUG: Start: Iteration 460
+2016-08-24 14:26:20,783 DEBUG: View 0 : 0.60663507109
+2016-08-24 14:26:20,793 DEBUG: View 1 : 0.668246445498
+2016-08-24 14:26:20,907 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:26:20,916 DEBUG: View 3 : 0.587677725118
+2016-08-24 14:26:22,282 DEBUG: Best view : MiRNA__
+2016-08-24 14:26:59,239 DEBUG: Start: Iteration 461
+2016-08-24 14:26:59,260 DEBUG: View 0 : 0.611374407583
+2016-08-24 14:26:59,269 DEBUG: View 1 : 0.469194312796
+2016-08-24 14:26:59,405 DEBUG: View 2 : 0.516587677725
+2016-08-24 14:26:59,415 DEBUG: View 3 : 0.516587677725
+2016-08-24 14:27:00,776 DEBUG: Best view : Methyl_
+2016-08-24 14:27:38,287 DEBUG: Start: Iteration 462
+2016-08-24 14:27:38,308 DEBUG: View 0 : 0.559241706161
+2016-08-24 14:27:38,317 DEBUG: View 1 : 0.587677725118
+2016-08-24 14:27:38,464 DEBUG: View 2 : 0.582938388626
+2016-08-24 14:27:38,474 DEBUG: View 3 : 0.60663507109
+2016-08-24 14:27:39,847 DEBUG: Best view : Clinic_
+2016-08-24 14:28:18,037 DEBUG: Start: Iteration 463
+2016-08-24 14:28:18,062 DEBUG: View 0 : 0.436018957346
+2016-08-24 14:28:18,072 DEBUG: View 1 : 0.630331753555
+2016-08-24 14:28:18,228 DEBUG: View 2 : 0.554502369668
+2016-08-24 14:28:18,237 DEBUG: View 3 : 0.611374407583
+2016-08-24 14:28:19,596 DEBUG: Best view : Clinic_
+2016-08-24 14:28:56,597 DEBUG: Start: Iteration 464
+2016-08-24 14:28:56,619 DEBUG: View 0 : 0.57345971564
+2016-08-24 14:28:56,628 DEBUG: View 1 : 0.677725118483
+2016-08-24 14:28:56,758 DEBUG: View 2 : 0.511848341232
+2016-08-24 14:28:56,767 DEBUG: View 3 : 0.682464454976
+2016-08-24 14:28:58,130 DEBUG: Best view : Clinic_
+2016-08-24 14:29:35,413 DEBUG: Start: Iteration 465
+2016-08-24 14:29:35,434 DEBUG: View 0 : 0.663507109005
+2016-08-24 14:29:35,444 DEBUG: View 1 : 0.597156398104
+2016-08-24 14:29:35,556 DEBUG: View 2 : 0.535545023697
+2016-08-24 14:29:35,566 DEBUG: View 3 : 0.582938388626
+2016-08-24 14:29:36,961 DEBUG: Best view : Methyl_
+2016-08-24 14:30:14,881 DEBUG: Start: Iteration 466
+2016-08-24 14:30:14,902 DEBUG: View 0 : 0.620853080569
+2016-08-24 14:30:14,912 DEBUG: View 1 : 0.597156398104
+2016-08-24 14:30:15,025 DEBUG: View 2 : 0.54028436019
+2016-08-24 14:30:15,035 DEBUG: View 3 : 0.706161137441
+2016-08-24 14:30:16,512 DEBUG: Best view : Clinic_
+2016-08-24 14:30:55,095 DEBUG: Start: Iteration 467
+2016-08-24 14:30:55,116 DEBUG: View 0 : 0.407582938389
+2016-08-24 14:30:55,126 DEBUG: View 1 : 0.587677725118
+2016-08-24 14:30:55,250 DEBUG: View 2 : 0.611374407583
+2016-08-24 14:30:55,259 DEBUG: View 3 : 0.554502369668
+2016-08-24 14:30:56,684 DEBUG: Best view : RANSeq_
+2016-08-24 14:31:34,469 DEBUG: Start: Iteration 468
+2016-08-24 14:31:34,489 DEBUG: View 0 : 0.668246445498
+2016-08-24 14:31:34,498 DEBUG: View 1 : 0.668246445498
+2016-08-24 14:31:34,620 DEBUG: View 2 : 0.483412322275
+2016-08-24 14:31:34,629 DEBUG: View 3 : 0.654028436019
+2016-08-24 14:31:36,027 DEBUG: Best view : Methyl_
+2016-08-24 14:32:14,205 DEBUG: Start: Iteration 469
+2016-08-24 14:32:14,226 DEBUG: View 0 : 0.535545023697
+2016-08-24 14:32:14,235 DEBUG: View 1 : 0.739336492891
+2016-08-24 14:32:14,353 DEBUG: View 2 : 0.649289099526
+2016-08-24 14:32:14,362 DEBUG: View 3 : 0.601895734597
+2016-08-24 14:32:15,787 DEBUG: Best view : MiRNA__
+2016-08-24 14:32:54,091 DEBUG: Start: Iteration 470
+2016-08-24 14:32:54,114 DEBUG: View 0 : 0.60663507109
+2016-08-24 14:32:54,124 DEBUG: View 1 : 0.502369668246
+2016-08-24 14:32:54,243 DEBUG: View 2 : 0.578199052133
+2016-08-24 14:32:54,253 DEBUG: View 3 : 0.568720379147
+2016-08-24 14:32:55,737 DEBUG: Best view : Methyl_
+2016-08-24 14:33:34,003 DEBUG: Start: Iteration 471
+2016-08-24 14:33:34,024 DEBUG: View 0 : 0.559241706161
+2016-08-24 14:33:34,033 DEBUG: View 1 : 0.720379146919
+2016-08-24 14:33:34,146 DEBUG: View 2 : 0.549763033175
+2016-08-24 14:33:34,156 DEBUG: View 3 : 0.654028436019
+2016-08-24 14:33:35,545 DEBUG: Best view : MiRNA__
+2016-08-24 14:34:13,876 DEBUG: Start: Iteration 472
+2016-08-24 14:34:13,897 DEBUG: View 0 : 0.611374407583
+2016-08-24 14:34:13,906 DEBUG: View 1 : 0.616113744076
+2016-08-24 14:34:14,030 DEBUG: View 2 : 0.578199052133
+2016-08-24 14:34:14,040 DEBUG: View 3 : 0.658767772512
+2016-08-24 14:34:15,463 DEBUG: Best view : Clinic_
+2016-08-24 14:34:54,173 DEBUG: Start: Iteration 473
+2016-08-24 14:34:54,194 DEBUG: View 0 : 0.611374407583
+2016-08-24 14:34:54,203 DEBUG: View 1 : 0.611374407583
+2016-08-24 14:34:54,329 DEBUG: View 2 : 0.545023696682
+2016-08-24 14:34:54,339 DEBUG: View 3 : 0.554502369668
+2016-08-24 14:34:55,732 DEBUG: Best view : MiRNA__
+2016-08-24 14:35:34,082 DEBUG: Start: Iteration 474
+2016-08-24 14:35:34,103 DEBUG: View 0 : 0.511848341232
+2016-08-24 14:35:34,112 DEBUG: View 1 : 0.75355450237
+2016-08-24 14:35:34,239 DEBUG: View 2 : 0.473933649289
+2016-08-24 14:35:34,249 DEBUG: View 3 : 0.620853080569
+2016-08-24 14:35:35,798 DEBUG: Best view : MiRNA__
+2016-08-24 14:36:14,378 DEBUG: Start: Iteration 475
+2016-08-24 14:36:14,399 DEBUG: View 0 : 0.516587677725
+2016-08-24 14:36:14,408 DEBUG: View 1 : 0.507109004739
+2016-08-24 14:36:14,537 DEBUG: View 2 : 0.611374407583
+2016-08-24 14:36:14,547 DEBUG: View 3 : 0.592417061611
+2016-08-24 14:36:16,022 DEBUG: Best view : RANSeq_
+2016-08-24 14:36:54,417 DEBUG: Start: Iteration 476
+2016-08-24 14:36:54,438 DEBUG: View 0 : 0.668246445498
+2016-08-24 14:36:54,448 DEBUG: View 1 : 0.687203791469
+2016-08-24 14:36:54,562 DEBUG: View 2 : 0.497630331754
+2016-08-24 14:36:54,572 DEBUG: View 3 : 0.578199052133
+2016-08-24 14:36:56,022 DEBUG: Best view : MiRNA__
+2016-08-24 14:37:33,927 DEBUG: Start: Iteration 477
+2016-08-24 14:37:33,948 DEBUG: View 0 : 0.587677725118
+2016-08-24 14:37:33,957 DEBUG: View 1 : 0.374407582938
+2016-08-24 14:37:34,072 DEBUG: View 2 : 0.483412322275
+2016-08-24 14:37:34,082 DEBUG: View 3 : 0.563981042654
+2016-08-24 14:37:35,484 DEBUG: Best view : Clinic_
+2016-08-24 14:38:13,694 DEBUG: Start: Iteration 478
+2016-08-24 14:38:13,715 DEBUG: View 0 : 0.554502369668
+2016-08-24 14:38:13,725 DEBUG: View 1 : 0.554502369668
+2016-08-24 14:38:13,838 DEBUG: View 2 : 0.601895734597
+2016-08-24 14:38:13,848 DEBUG: View 3 : 0.554502369668
+2016-08-24 14:38:15,290 DEBUG: Best view : RANSeq_
+2016-08-24 14:38:53,757 DEBUG: Start: Iteration 479
+2016-08-24 14:38:53,778 DEBUG: View 0 : 0.554502369668
+2016-08-24 14:38:53,788 DEBUG: View 1 : 0.630331753555
+2016-08-24 14:38:53,912 DEBUG: View 2 : 0.516587677725
+2016-08-24 14:38:53,922 DEBUG: View 3 : 0.625592417062
+2016-08-24 14:38:55,346 DEBUG: Best view : Clinic_
+2016-08-24 14:39:34,401 DEBUG: Start: Iteration 480
+2016-08-24 14:39:34,425 DEBUG: View 0 : 0.545023696682
+2016-08-24 14:39:34,440 DEBUG: View 1 : 0.668246445498
+2016-08-24 14:39:34,579 DEBUG: View 2 : 0.582938388626
+2016-08-24 14:39:34,589 DEBUG: View 3 : 0.691943127962
+2016-08-24 14:39:36,125 DEBUG: Best view : Clinic_
+2016-08-24 14:40:14,887 DEBUG: Start: Iteration 481
+2016-08-24 14:40:14,908 DEBUG: View 0 : 0.54028436019
+2016-08-24 14:40:14,918 DEBUG: View 1 : 0.668246445498
+2016-08-24 14:40:15,053 DEBUG: View 2 : 0.507109004739
+2016-08-24 14:40:15,066 DEBUG: View 3 : 0.535545023697
+2016-08-24 14:40:16,577 DEBUG: Best view : MiRNA__
+2016-08-24 14:40:55,468 DEBUG: Start: Iteration 482
+2016-08-24 14:40:55,489 DEBUG: View 0 : 0.488151658768
+2016-08-24 14:40:55,499 DEBUG: View 1 : 0.630331753555
+2016-08-24 14:40:55,629 DEBUG: View 2 : 0.554502369668
+2016-08-24 14:40:55,640 DEBUG: View 3 : 0.592417061611
+2016-08-24 14:40:57,059 DEBUG: Best view : MiRNA__
+2016-08-24 14:41:35,975 DEBUG: Start: Iteration 483
+2016-08-24 14:41:35,995 DEBUG: View 0 : 0.578199052133
+2016-08-24 14:41:36,005 DEBUG: View 1 : 0.601895734597
+2016-08-24 14:41:36,148 DEBUG: View 2 : 0.54028436019
+2016-08-24 14:41:36,160 DEBUG: View 3 : 0.563981042654
+2016-08-24 14:41:37,599 DEBUG: Best view : Clinic_
+2016-08-24 14:42:16,484 DEBUG: Start: Iteration 484
+2016-08-24 14:42:16,505 DEBUG: View 0 : 0.611374407583
+2016-08-24 14:42:16,515 DEBUG: View 1 : 0.535545023697
+2016-08-24 14:42:16,644 DEBUG: View 2 : 0.60663507109
+2016-08-24 14:42:16,656 DEBUG: View 3 : 0.701421800948
+2016-08-24 14:42:18,100 DEBUG: Best view : Clinic_
+2016-08-24 14:42:57,361 DEBUG: Start: Iteration 485
+2016-08-24 14:42:57,385 DEBUG: View 0 : 0.563981042654
+2016-08-24 14:42:57,394 DEBUG: View 1 : 0.398104265403
+2016-08-24 14:42:57,528 DEBUG: View 2 : 0.582938388626
+2016-08-24 14:42:57,540 DEBUG: View 3 : 0.587677725118
+2016-08-24 14:42:59,092 DEBUG: Best view : Clinic_
+2016-08-24 14:43:38,145 DEBUG: Start: Iteration 486
+2016-08-24 14:43:38,166 DEBUG: View 0 : 0.45971563981
+2016-08-24 14:43:38,176 DEBUG: View 1 : 0.582938388626
+2016-08-24 14:43:38,310 DEBUG: View 2 : 0.616113744076
+2016-08-24 14:43:38,322 DEBUG: View 3 : 0.620853080569
+2016-08-24 14:43:39,765 DEBUG: Best view : Clinic_
+2016-08-24 14:44:19,272 DEBUG: Start: Iteration 487
+2016-08-24 14:44:19,297 DEBUG: View 0 : 0.554502369668
+2016-08-24 14:44:19,308 DEBUG: View 1 : 0.668246445498
+2016-08-24 14:44:19,463 DEBUG: View 2 : 0.526066350711
+2016-08-24 14:44:19,476 DEBUG: View 3 : 0.649289099526
+2016-08-24 14:44:20,936 DEBUG: Best view : Clinic_
+2016-08-24 14:45:00,133 DEBUG: Start: Iteration 488
+2016-08-24 14:45:00,155 DEBUG: View 0 : 0.507109004739
+2016-08-24 14:45:00,164 DEBUG: View 1 : 0.635071090047
+2016-08-24 14:45:00,292 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:45:00,304 DEBUG: View 3 : 0.568720379147
+2016-08-24 14:45:01,790 DEBUG: Best view : MiRNA__
+2016-08-24 14:45:40,751 DEBUG: Start: Iteration 489
+2016-08-24 14:45:40,770 DEBUG: View 0 : 0.549763033175
+2016-08-24 14:45:40,780 DEBUG: View 1 : 0.488151658768
+2016-08-24 14:45:40,918 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:45:40,930 DEBUG: View 3 : 0.568720379147
+2016-08-24 14:45:42,383 DEBUG: Best view : Clinic_
+2016-08-24 14:46:21,819 DEBUG: Start: Iteration 490
+2016-08-24 14:46:21,840 DEBUG: View 0 : 0.450236966825
+2016-08-24 14:46:21,850 DEBUG: View 1 : 0.535545023697
+2016-08-24 14:46:21,980 DEBUG: View 2 : 0.611374407583
+2016-08-24 14:46:21,991 DEBUG: View 3 : 0.511848341232
+2016-08-24 14:46:23,445 DEBUG: Best view : RANSeq_
+2016-08-24 14:47:03,443 DEBUG: Start: Iteration 491
+2016-08-24 14:47:03,465 DEBUG: View 0 : 0.492890995261
+2016-08-24 14:47:03,475 DEBUG: View 1 : 0.630331753555
+2016-08-24 14:47:03,604 DEBUG: View 2 : 0.549763033175
+2016-08-24 14:47:03,616 DEBUG: View 3 : 0.582938388626
+2016-08-24 14:47:05,066 DEBUG: Best view : MiRNA__
+2016-08-24 14:47:44,382 DEBUG: Start: Iteration 492
+2016-08-24 14:47:44,404 DEBUG: View 0 : 0.654028436019
+2016-08-24 14:47:44,413 DEBUG: View 1 : 0.478672985782
+2016-08-24 14:47:44,543 DEBUG: View 2 : 0.57345971564
+2016-08-24 14:47:44,555 DEBUG: View 3 : 0.568720379147
+2016-08-24 14:47:46,025 DEBUG: Best view : Methyl_
+2016-08-24 14:48:26,539 DEBUG: Start: Iteration 493
+2016-08-24 14:48:26,562 DEBUG: View 0 : 0.421800947867
+2016-08-24 14:48:26,571 DEBUG: View 1 : 0.677725118483
+2016-08-24 14:48:26,712 DEBUG: View 2 : 0.516587677725
+2016-08-24 14:48:26,725 DEBUG: View 3 : 0.625592417062
+2016-08-24 14:48:28,443 DEBUG: Best view : MiRNA__
+2016-08-24 14:49:08,581 DEBUG: Start: Iteration 494
+2016-08-24 14:49:08,602 DEBUG: View 0 : 0.502369668246
+2016-08-24 14:49:08,612 DEBUG: View 1 : 0.502369668246
+2016-08-24 14:49:08,767 DEBUG: View 2 : 0.587677725118
+2016-08-24 14:49:08,776 DEBUG: View 3 : 0.554502369668
+2016-08-24 14:49:10,262 DEBUG: Best view : RANSeq_
+2016-08-24 14:49:49,722 DEBUG: Start: Iteration 495
+2016-08-24 14:49:49,742 DEBUG: View 0 : 0.497630331754
+2016-08-24 14:49:49,752 DEBUG: View 1 : 0.488151658768
+2016-08-24 14:49:49,869 DEBUG: View 2 : 0.563981042654
+2016-08-24 14:49:49,878 DEBUG: View 3 : 0.60663507109
+2016-08-24 14:49:51,372 DEBUG: Best view : Clinic_
+2016-08-24 14:50:31,344 DEBUG: Start: Iteration 496
+2016-08-24 14:50:31,368 DEBUG: View 0 : 0.464454976303
+2016-08-24 14:50:31,379 DEBUG: View 1 : 0.563981042654
+2016-08-24 14:50:31,540 DEBUG: View 2 : 0.535545023697
+2016-08-24 14:50:31,551 DEBUG: View 3 : 0.677725118483
+2016-08-24 14:50:33,064 DEBUG: Best view : Clinic_
+2016-08-24 14:51:12,832 DEBUG: Start: Iteration 497
+2016-08-24 14:51:12,853 DEBUG: View 0 : 0.436018957346
+2016-08-24 14:51:12,862 DEBUG: View 1 : 0.274881516588
+2016-08-24 14:51:13,000 DEBUG: View 2 : 0.492890995261
+2016-08-24 14:51:13,010 DEBUG: View 3 : 0.592417061611
+2016-08-24 14:51:14,493 DEBUG: Best view : Clinic_
+2016-08-24 14:51:54,078 DEBUG: Start: Iteration 498
+2016-08-24 14:51:54,099 DEBUG: View 0 : 0.696682464455
+2016-08-24 14:51:54,109 DEBUG: View 1 : 0.649289099526
+2016-08-24 14:51:54,236 DEBUG: View 2 : 0.545023696682
+2016-08-24 14:51:54,247 DEBUG: View 3 : 0.511848341232
+2016-08-24 14:51:55,773 DEBUG: Best view : Methyl_
+2016-08-24 14:52:35,842 DEBUG: Start: Iteration 499
+2016-08-24 14:52:35,863 DEBUG: View 0 : 0.620853080569
+2016-08-24 14:52:35,873 DEBUG: View 1 : 0.587677725118
+2016-08-24 14:52:35,995 DEBUG: View 2 : 0.63981042654
+2016-08-24 14:52:36,005 DEBUG: View 3 : 0.677725118483
+2016-08-24 14:52:37,485 DEBUG: Best view : Clinic_
+2016-08-24 14:53:17,616 DEBUG: Start: Iteration 500
+2016-08-24 14:53:17,637 DEBUG: View 0 : 0.563981042654
+2016-08-24 14:53:17,648 DEBUG: View 1 : 0.554502369668
+2016-08-24 14:53:17,772 DEBUG: View 2 : 0.563981042654
+2016-08-24 14:53:17,782 DEBUG: View 3 : 0.63981042654
+2016-08-24 14:53:19,276 DEBUG: Best view : Clinic_
+2016-08-24 14:53:59,709 DEBUG: Start: Iteration 501
+2016-08-24 14:53:59,730 DEBUG: View 0 : 0.549763033175
+2016-08-24 14:53:59,740 DEBUG: View 1 : 0.682464454976
+2016-08-24 14:53:59,869 DEBUG: View 2 : 0.611374407583
+2016-08-24 14:53:59,879 DEBUG: View 3 : 0.502369668246
+2016-08-24 14:54:01,355 DEBUG: Best view : MiRNA__
+2016-08-24 14:54:42,269 DEBUG: 6.43108861106e-05 proche de zero ?
+2016-08-24 14:54:42,269 DEBUG: Start: Iteration 502
+2016-08-24 14:54:42,293 DEBUG: View 0 : 0.350710900474
+2016-08-24 14:54:42,304 DEBUG: View 1 : 0.488151658768
+2016-08-24 14:54:42,455 DEBUG: View 2 : 0.582938388626
+2016-08-24 14:54:42,466 DEBUG: View 3 : 0.578199052133
+2016-08-24 14:54:43,961 DEBUG: Best view : Clinic_
+2016-08-24 14:55:24,658 DEBUG: 6.42019701749e-05 proche de zero ?
+2016-08-24 14:55:24,658 DEBUG: Start: Iteration 503
+2016-08-24 14:55:24,684 DEBUG: View 0 : 0.521327014218
+2016-08-24 14:55:24,695 DEBUG: View 1 : 0.559241706161
+2016-08-24 14:55:24,844 DEBUG: View 2 : 0.559241706161
+2016-08-24 14:55:24,855 DEBUG: View 3 : 0.545023696682
+2016-08-24 14:55:26,433 DEBUG: Best view : RANSeq_
+2016-08-24 14:56:07,371 DEBUG: 6.40932219808e-05 proche de zero ?
+2016-08-24 14:56:07,372 DEBUG: Start: Iteration 504
+2016-08-24 14:56:07,396 DEBUG: View 0 : 0.582938388626
+2016-08-24 14:56:07,410 DEBUG: View 1 : 0.516587677725
+2016-08-24 14:56:07,564 DEBUG: View 2 : 0.464454976303
+2016-08-24 14:56:07,576 DEBUG: View 3 : 0.545023696682
+2016-08-24 14:56:09,062 DEBUG: Best view : Clinic_
+2016-08-24 14:56:49,356 DEBUG: 6.39846425015e-05 proche de zero ?
+2016-08-24 14:56:49,357 DEBUG: Start: Iteration 505
+2016-08-24 14:56:49,386 DEBUG: View 0 : 0.469194312796
+2016-08-24 14:56:49,398 DEBUG: View 1 : 0.57345971564
+2016-08-24 14:56:49,520 DEBUG: View 2 : 0.511848341232
+2016-08-24 14:56:49,533 DEBUG: View 3 : 0.63981042654
+2016-08-24 14:56:51,030 DEBUG: Best view : Clinic_
+2016-08-24 14:57:31,246 DEBUG: 6.38762326861e-05 proche de zero ?
+2016-08-24 14:57:31,246 DEBUG: Start: Iteration 506
+2016-08-24 14:57:31,276 DEBUG: View 0 : 0.445497630332
+2016-08-24 14:57:31,294 DEBUG: View 1 : 0.63981042654
+2016-08-24 14:57:31,445 DEBUG: View 2 : 0.625592417062
+2016-08-24 14:57:31,457 DEBUG: View 3 : 0.592417061611
+2016-08-24 14:57:32,969 DEBUG: Best view : RANSeq_
+2016-08-24 14:58:13,419 DEBUG: 6.37679934601e-05 proche de zero ?
+2016-08-24 14:58:13,420 DEBUG: Start: Iteration 507
+2016-08-24 14:58:13,444 DEBUG: View 0 : 0.388625592417
+2016-08-24 14:58:13,455 DEBUG: View 1 : 0.677725118483
+2016-08-24 14:58:13,595 DEBUG: View 2 : 0.521327014218
+2016-08-24 14:58:13,608 DEBUG: View 3 : 0.563981042654
+2016-08-24 14:58:15,125 DEBUG: Best view : MiRNA__
+2016-08-24 14:58:56,247 DEBUG: 6.36473362773e-05 proche de zero ?
+2016-08-24 14:58:56,247 DEBUG: Start: Iteration 508
+2016-08-24 14:58:56,278 DEBUG: View 0 : 0.611374407583
+2016-08-24 14:58:56,287 DEBUG: View 1 : 0.497630331754
+2016-08-24 14:58:56,432 DEBUG: View 2 : 0.578199052133
+2016-08-24 14:58:56,444 DEBUG: View 3 : 0.635071090047
+2016-08-24 14:58:57,984 DEBUG: Best view : Clinic_
+2016-08-24 14:59:39,248 DEBUG: 6.35269610662e-05 proche de zero ?
+2016-08-24 14:59:39,249 DEBUG: Start: Iteration 509
+2016-08-24 14:59:39,273 DEBUG: View 0 : 0.454976303318
+2016-08-24 14:59:39,285 DEBUG: View 1 : 0.654028436019
+2016-08-24 14:59:39,428 DEBUG: View 2 : 0.587677725118
+2016-08-24 14:59:39,439 DEBUG: View 3 : 0.691943127962
+2016-08-24 14:59:40,975 DEBUG: Best view : Clinic_
+2016-08-24 15:00:21,819 DEBUG: 6.34193719181e-05 proche de zero ?
+2016-08-24 15:00:21,820 DEBUG: Start: Iteration 510
+2016-08-24 15:00:21,845 DEBUG: View 0 : 0.587677725118
+2016-08-24 15:00:21,856 DEBUG: View 1 : 0.663507109005
+2016-08-24 15:00:21,994 DEBUG: View 2 : 0.582938388626
+2016-08-24 15:00:22,011 DEBUG: View 3 : 0.601895734597
+2016-08-24 15:00:23,521 DEBUG: Best view : MiRNA__
+2016-08-24 15:01:04,544 DEBUG: 6.33119559779e-05 proche de zero ?
+2016-08-24 15:01:04,544 DEBUG: Start: Iteration 511
+2016-08-24 15:01:04,569 DEBUG: View 0 : 0.341232227488
+2016-08-24 15:01:04,579 DEBUG: View 1 : 0.421800947867
+2016-08-24 15:01:04,714 DEBUG: View 2 : 0.559241706161
+2016-08-24 15:01:04,727 DEBUG: View 3 : 0.57345971564
+2016-08-24 15:01:06,266 DEBUG: Best view : Clinic_
+2016-08-24 15:01:47,018 DEBUG: 6.32047140654e-05 proche de zero ?
+2016-08-24 15:01:47,018 DEBUG: Start: Iteration 512
+2016-08-24 15:01:47,042 DEBUG: View 0 : 0.526066350711
+2016-08-24 15:01:47,053 DEBUG: View 1 : 0.364928909953
+2016-08-24 15:01:47,210 DEBUG: View 2 : 0.511848341232
+2016-08-24 15:01:47,220 DEBUG: View 3 : 0.630331753555
+2016-08-24 15:01:48,727 DEBUG: Best view : Clinic_
+2016-08-24 15:02:29,648 DEBUG: 6.30976469783e-05 proche de zero ?
+2016-08-24 15:02:29,648 DEBUG: Start: Iteration 513
+2016-08-24 15:02:29,673 DEBUG: View 0 : 0.601895734597
+2016-08-24 15:02:29,685 DEBUG: View 1 : 0.473933649289
+2016-08-24 15:02:29,850 DEBUG: View 2 : 0.625592417062
+2016-08-24 15:02:29,859 DEBUG: View 3 : 0.710900473934
+2016-08-24 15:02:31,405 DEBUG: Best view : Clinic_
+2016-08-24 15:03:12,445 DEBUG: 6.29907554935e-05 proche de zero ?
+2016-08-24 15:03:12,445 DEBUG: Start: Iteration 514
+2016-08-24 15:03:12,470 DEBUG: View 0 : 0.60663507109
+2016-08-24 15:03:12,481 DEBUG: View 1 : 0.677725118483
+2016-08-24 15:03:12,621 DEBUG: View 2 : 0.60663507109
+2016-08-24 15:03:12,637 DEBUG: View 3 : 0.559241706161
+2016-08-24 15:03:14,153 DEBUG: Best view : MiRNA__
+2016-08-24 15:03:55,418 DEBUG: 6.28840403669e-05 proche de zero ?
+2016-08-24 15:03:55,418 DEBUG: Start: Iteration 515
+2016-08-24 15:03:55,452 DEBUG: View 0 : 0.672985781991
+2016-08-24 15:03:55,469 DEBUG: View 1 : 0.729857819905
+2016-08-24 15:03:55,590 DEBUG: View 2 : 0.526066350711
+2016-08-24 15:03:55,599 DEBUG: View 3 : 0.616113744076
+2016-08-24 15:03:57,134 DEBUG: Best view : MiRNA__
+2016-08-24 15:04:38,371 DEBUG: 6.27775023341e-05 proche de zero ?
+2016-08-24 15:04:38,371 DEBUG: Start: Iteration 516
+2016-08-24 15:04:38,405 DEBUG: View 0 : 0.616113744076
+2016-08-24 15:04:38,421 DEBUG: View 1 : 0.625592417062
+2016-08-24 15:04:38,562 DEBUG: View 2 : 0.488151658768
+2016-08-24 15:04:38,571 DEBUG: View 3 : 0.554502369668
+2016-08-24 15:04:40,107 DEBUG: Best view : MiRNA__
+2016-08-24 15:05:21,425 DEBUG: 6.26711421105e-05 proche de zero ?
+2016-08-24 15:05:21,426 DEBUG: Start: Iteration 517
+2016-08-24 15:05:21,451 DEBUG: View 0 : 0.582938388626
+2016-08-24 15:05:21,462 DEBUG: View 1 : 0.559241706161
+2016-08-24 15:05:21,590 DEBUG: View 2 : 0.582938388626
+2016-08-24 15:05:21,599 DEBUG: View 3 : 0.54028436019
+2016-08-24 15:05:23,158 DEBUG: Best view : RANSeq_
+2016-08-24 15:06:04,833 DEBUG: 6.25649603915e-05 proche de zero ?
+2016-08-24 15:06:04,833 DEBUG: Start: Iteration 518
+2016-08-24 15:06:04,858 DEBUG: View 0 : 0.616113744076
+2016-08-24 15:06:04,869 DEBUG: View 1 : 0.473933649289
+2016-08-24 15:06:05,004 DEBUG: View 2 : 0.57345971564
+2016-08-24 15:06:05,014 DEBUG: View 3 : 0.578199052133
+2016-08-24 15:06:06,594 DEBUG: Best view : Clinic_
+2016-08-24 15:06:48,955 DEBUG: 6.24589578535e-05 proche de zero ?
+2016-08-24 15:06:48,956 DEBUG: Start: Iteration 519
+2016-08-24 15:06:48,980 DEBUG: View 0 : 0.635071090047
+2016-08-24 15:06:48,991 DEBUG: View 1 : 0.57345971564
+2016-08-24 15:06:49,152 DEBUG: View 2 : 0.469194312796
+2016-08-24 15:06:49,163 DEBUG: View 3 : 0.710900473934
+2016-08-24 15:06:50,826 DEBUG: Best view : Clinic_
+2016-08-24 15:07:33,656 DEBUG: 6.23531351532e-05 proche de zero ?
+2016-08-24 15:07:33,656 DEBUG: Start: Iteration 520
+2016-08-24 15:07:33,680 DEBUG: View 0 : 0.554502369668
+2016-08-24 15:07:33,691 DEBUG: View 1 : 0.800947867299
+2016-08-24 15:07:33,850 DEBUG: View 2 : 0.592417061611
+2016-08-24 15:07:33,859 DEBUG: View 3 : 0.649289099526
+2016-08-24 15:07:35,393 DEBUG: Best view : MiRNA__
+2016-08-24 15:08:17,754 DEBUG: 6.22474929289e-05 proche de zero ?
+2016-08-24 15:08:17,755 DEBUG: Start: Iteration 521
+2016-08-24 15:08:17,779 DEBUG: View 0 : 0.625592417062
+2016-08-24 15:08:17,790 DEBUG: View 1 : 0.654028436019
+2016-08-24 15:08:17,926 DEBUG: View 2 : 0.578199052133
+2016-08-24 15:08:17,935 DEBUG: View 3 : 0.597156398104
+2016-08-24 15:08:19,472 DEBUG: Best view : MiRNA__
+2016-08-24 15:09:00,815 DEBUG: 6.21420318002e-05 proche de zero ?
+2016-08-24 15:09:00,815 DEBUG: Start: Iteration 522
+2016-08-24 15:09:00,840 DEBUG: View 0 : 0.578199052133
+2016-08-24 15:09:00,852 DEBUG: View 1 : 0.644549763033
+2016-08-24 15:09:00,991 DEBUG: View 2 : 0.60663507109
+2016-08-24 15:09:01,000 DEBUG: View 3 : 0.488151658768
+2016-08-24 15:09:02,525 DEBUG: Best view : MiRNA__
+2016-08-24 15:09:44,500 DEBUG: 6.20367523684e-05 proche de zero ?
+2016-08-24 15:09:44,501 DEBUG: Start: Iteration 523
+2016-08-24 15:09:44,525 DEBUG: View 0 : 0.492890995261
+2016-08-24 15:09:44,535 DEBUG: View 1 : 0.720379146919
+2016-08-24 15:09:44,661 DEBUG: View 2 : 0.587677725118
+2016-08-24 15:09:44,670 DEBUG: View 3 : 0.630331753555
+2016-08-24 15:09:46,207 DEBUG: Best view : MiRNA__
+2016-08-24 15:10:29,196 DEBUG: 6.19197235513e-05 proche de zero ?
+2016-08-24 15:10:29,196 DEBUG: Start: Iteration 524
+2016-08-24 15:10:29,412 DEBUG: View 0 : 0.601895734597
+2016-08-24 15:10:29,438 DEBUG: View 1 : 0.469194312796
+2016-08-24 15:10:29,851 DEBUG: View 2 : 0.597156398104
+2016-08-24 15:10:29,862 DEBUG: View 3 : 0.549763033175
+2016-08-24 15:10:31,523 DEBUG: Best view : Methyl_
+2016-08-24 15:11:15,637 DEBUG: 6.18148708249e-05 proche de zero ?
+2016-08-24 15:11:15,637 DEBUG: Start: Iteration 525
+2016-08-24 15:11:15,662 DEBUG: View 0 : 0.663507109005
+2016-08-24 15:11:15,674 DEBUG: View 1 : 0.677725118483
+2016-08-24 15:11:15,811 DEBUG: View 2 : 0.559241706161
+2016-08-24 15:11:15,821 DEBUG: View 3 : 0.582938388626
+2016-08-24 15:11:17,608 DEBUG: Best view : MiRNA__
+2016-08-24 15:12:01,649 DEBUG: 6.17102011088e-05 proche de zero ?
+2016-08-24 15:12:01,650 DEBUG: Start: Iteration 526
+2016-08-24 15:12:01,674 DEBUG: View 0 : 0.284360189573
+2016-08-24 15:12:01,685 DEBUG: View 1 : 0.587677725118
+2016-08-24 15:12:01,813 DEBUG: View 2 : 0.545023696682
+2016-08-24 15:12:01,822 DEBUG: View 3 : 0.57345971564
+2016-08-24 15:12:03,531 DEBUG: Best view : Clinic_
+2016-08-24 15:12:47,530 DEBUG: 6.16057149375e-05 proche de zero ?
+2016-08-24 15:12:47,531 DEBUG: Start: Iteration 527
+2016-08-24 15:12:47,568 DEBUG: View 0 : 0.687203791469
+2016-08-24 15:12:47,585 DEBUG: View 1 : 0.578199052133
+2016-08-24 15:12:47,742 DEBUG: View 2 : 0.658767772512
+2016-08-24 15:12:47,753 DEBUG: View 3 : 0.630331753555
+2016-08-24 15:12:49,328 DEBUG: Best view : Methyl_
+2016-08-24 15:13:31,667 DEBUG: 6.15014128287e-05 proche de zero ?
+2016-08-24 15:13:31,668 DEBUG: Start: Iteration 528
+2016-08-24 15:13:31,692 DEBUG: View 0 : 0.507109004739
+2016-08-24 15:13:31,703 DEBUG: View 1 : 0.559241706161
+2016-08-24 15:13:31,836 DEBUG: View 2 : 0.526066350711
+2016-08-24 15:13:31,845 DEBUG: View 3 : 0.469194312796
+2016-08-24 15:13:33,405 DEBUG: Best view : MiRNA__
+2016-08-24 15:14:16,032 DEBUG: 6.13972952838e-05 proche de zero ?
+2016-08-24 15:14:16,032 DEBUG: Start: Iteration 529
+2016-08-24 15:14:16,055 DEBUG: View 0 : 0.436018957346
+2016-08-24 15:14:16,064 DEBUG: View 1 : 0.654028436019
+2016-08-24 15:14:16,191 DEBUG: View 2 : 0.635071090047
+2016-08-24 15:14:16,200 DEBUG: View 3 : 0.57345971564
+2016-08-24 15:14:18,060 DEBUG: Best view : RANSeq_
+2016-08-24 15:15:02,190 DEBUG: 6.12933627878e-05 proche de zero ?
+2016-08-24 15:15:02,190 DEBUG: Start: Iteration 530
+2016-08-24 15:15:02,219 DEBUG: View 0 : 0.635071090047
+2016-08-24 15:15:02,236 DEBUG: View 1 : 0.649289099526
+2016-08-24 15:15:02,391 DEBUG: View 2 : 0.587677725118
+2016-08-24 15:15:02,408 DEBUG: View 3 : 0.530805687204
+2016-08-24 15:15:04,103 DEBUG: Best view : MiRNA__
+2016-08-24 15:15:47,898 DEBUG: 6.11896158096e-05 proche de zero ?
+2016-08-24 15:15:47,899 DEBUG: Start: Iteration 531
+2016-08-24 15:15:47,937 DEBUG: View 0 : 0.469194312796
+2016-08-24 15:15:47,957 DEBUG: View 1 : 0.45971563981
+2016-08-24 15:15:48,105 DEBUG: View 2 : 0.549763033175
+2016-08-24 15:15:48,116 DEBUG: View 3 : 0.597156398104
+2016-08-24 15:15:49,811 DEBUG: Best view : Clinic_
+2016-08-24 15:16:34,198 DEBUG: 6.10860548028e-05 proche de zero ?
+2016-08-24 15:16:34,198 DEBUG: Start: Iteration 532
+2016-08-24 15:16:34,225 DEBUG: View 0 : 0.54028436019
+2016-08-24 15:16:34,238 DEBUG: View 1 : 0.687203791469
+2016-08-24 15:16:34,404 DEBUG: View 2 : 0.620853080569
+2016-08-24 15:16:34,415 DEBUG: View 3 : 0.649289099526
+2016-08-24 15:16:36,063 DEBUG: Best view : MiRNA__
+2016-08-24 15:17:20,598 DEBUG: 6.09826802051e-05 proche de zero ?
+2016-08-24 15:17:20,598 DEBUG: Start: Iteration 533
+2016-08-24 15:17:20,622 DEBUG: View 0 : 0.658767772512
+2016-08-24 15:17:20,633 DEBUG: View 1 : 0.620853080569
+2016-08-24 15:17:20,763 DEBUG: View 2 : 0.568720379147
+2016-08-24 15:17:20,775 DEBUG: View 3 : 0.54028436019
+2016-08-24 15:17:22,446 DEBUG: Best view : Methyl_
+2016-08-24 15:18:06,572 DEBUG: 6.08794924395e-05 proche de zero ?
+2016-08-24 15:18:06,572 DEBUG: Start: Iteration 534
+2016-08-24 15:18:06,596 DEBUG: View 0 : 0.601895734597
+2016-08-24 15:18:06,605 DEBUG: View 1 : 0.625592417062
+2016-08-24 15:18:06,755 DEBUG: View 2 : 0.492890995261
+2016-08-24 15:18:06,767 DEBUG: View 3 : 0.701421800948
+2016-08-24 15:18:08,389 DEBUG: Best view : Clinic_
+2016-08-24 15:18:54,278 DEBUG: 6.07764919137e-05 proche de zero ?
+2016-08-24 15:18:54,279 DEBUG: Start: Iteration 535
+2016-08-24 15:18:54,640 DEBUG: View 0 : 0.549763033175
+2016-08-24 15:18:54,662 DEBUG: View 1 : 0.421800947867
+2016-08-24 15:18:56,081 DEBUG: View 2 : 0.587677725118
+2016-08-24 15:18:56,104 DEBUG: View 3 : 0.630331753555
+2016-08-24 15:18:57,810 DEBUG: Best view : Clinic_
+2016-08-24 15:19:42,131 DEBUG: 6.0673679021e-05 proche de zero ?
+2016-08-24 15:19:42,131 DEBUG: Start: Iteration 536
+2016-08-24 15:19:42,156 DEBUG: View 0 : 0.578199052133
+2016-08-24 15:19:42,166 DEBUG: View 1 : 0.601895734597
+2016-08-24 15:19:42,283 DEBUG: View 2 : 0.54028436019
+2016-08-24 15:19:42,292 DEBUG: View 3 : 0.578199052133
+2016-08-24 15:19:43,942 DEBUG: Best view : Clinic_
+2016-08-24 15:20:27,085 DEBUG: 6.05710541401e-05 proche de zero ?
+2016-08-24 15:20:27,085 DEBUG: Start: Iteration 537
+2016-08-24 15:20:27,107 DEBUG: View 0 : 0.436018957346
+2016-08-24 15:20:27,117 DEBUG: View 1 : 0.473933649289
+2016-08-24 15:20:27,252 DEBUG: View 2 : 0.563981042654
+2016-08-24 15:20:27,265 DEBUG: View 3 : 0.696682464455
+2016-08-24 15:20:28,953 DEBUG: Best view : Clinic_
+2016-08-24 15:21:13,372 DEBUG: 6.04686176355e-05 proche de zero ?
+2016-08-24 15:21:13,372 DEBUG: Start: Iteration 538
+2016-08-24 15:21:13,397 DEBUG: View 0 : 0.587677725118
+2016-08-24 15:21:13,407 DEBUG: View 1 : 0.511848341232
+2016-08-24 15:21:13,545 DEBUG: View 2 : 0.511848341232
+2016-08-24 15:21:13,556 DEBUG: View 3 : 0.563981042654
+2016-08-24 15:21:15,151 DEBUG: Best view : Clinic_
+2016-08-24 15:21:59,346 DEBUG: 6.03663698579e-05 proche de zero ?
+2016-08-24 15:21:59,347 DEBUG: Start: Iteration 539
+2016-08-24 15:22:00,071 DEBUG: View 0 : 0.492890995261
+2016-08-24 15:22:00,093 DEBUG: View 1 : 0.620853080569
+2016-08-24 15:22:01,161 DEBUG: View 2 : 0.578199052133
+2016-08-24 15:22:01,193 DEBUG: View 3 : 0.672985781991
+2016-08-24 15:22:03,131 DEBUG: Best view : Clinic_
+2016-08-24 15:22:48,366 DEBUG: 6.02643111442e-05 proche de zero ?
+2016-08-24 15:22:48,366 DEBUG: Start: Iteration 540
+2016-08-24 15:22:48,389 DEBUG: View 0 : 0.630331753555
+2016-08-24 15:22:48,399 DEBUG: View 1 : 0.691943127962
+2016-08-24 15:22:48,523 DEBUG: View 2 : 0.563981042654
+2016-08-24 15:22:48,532 DEBUG: View 3 : 0.611374407583
+2016-08-24 15:22:50,133 DEBUG: Best view : MiRNA__
+2016-08-24 15:23:33,606 DEBUG: 6.01624418179e-05 proche de zero ?
+2016-08-24 15:23:33,607 DEBUG: Start: Iteration 541
+2016-08-24 15:23:33,630 DEBUG: View 0 : 0.592417061611
+2016-08-24 15:23:33,640 DEBUG: View 1 : 0.545023696682
+2016-08-24 15:23:33,771 DEBUG: View 2 : 0.635071090047
+2016-08-24 15:23:33,781 DEBUG: View 3 : 0.597156398104
+2016-08-24 15:23:35,443 DEBUG: Best view : RANSeq_
+2016-08-24 15:24:18,979 DEBUG: 6.0060762189e-05 proche de zero ?
+2016-08-24 15:24:18,979 DEBUG: Start: Iteration 542
+2016-08-24 15:24:19,003 DEBUG: View 0 : 0.630331753555
+2016-08-24 15:24:19,013 DEBUG: View 1 : 0.492890995261
+2016-08-24 15:24:19,135 DEBUG: View 2 : 0.592417061611
+2016-08-24 15:24:19,144 DEBUG: View 3 : 0.63981042654
+2016-08-24 15:24:20,737 DEBUG: Best view : Clinic_
+2016-08-24 15:25:03,911 DEBUG: 5.99592725547e-05 proche de zero ?
+2016-08-24 15:25:03,911 DEBUG: Start: Iteration 543
+2016-08-24 15:25:03,936 DEBUG: View 0 : 0.568720379147
+2016-08-24 15:25:03,946 DEBUG: View 1 : 0.601895734597
+2016-08-24 15:25:04,091 DEBUG: View 2 : 0.611374407583
+2016-08-24 15:25:04,104 DEBUG: View 3 : 0.601895734597
+2016-08-24 15:25:05,694 DEBUG: Best view : RANSeq_
+2016-08-24 15:25:49,244 DEBUG: 5.98579731994e-05 proche de zero ?
+2016-08-24 15:25:49,245 DEBUG: Start: Iteration 544
+2016-08-24 15:25:49,269 DEBUG: View 0 : 0.654028436019
+2016-08-24 15:25:49,278 DEBUG: View 1 : 0.625592417062
+2016-08-24 15:25:49,417 DEBUG: View 2 : 0.578199052133
+2016-08-24 15:25:49,430 DEBUG: View 3 : 0.60663507109
+2016-08-24 15:25:51,062 DEBUG: Best view : Methyl_
+2016-08-24 15:26:34,788 DEBUG: 5.97568643947e-05 proche de zero ?
+2016-08-24 15:26:34,788 DEBUG: Start: Iteration 545
+2016-08-24 15:26:34,813 DEBUG: View 0 : 0.450236966825
+2016-08-24 15:26:34,824 DEBUG: View 1 : 0.559241706161
+2016-08-24 15:26:34,971 DEBUG: View 2 : 0.483412322275
+2016-08-24 15:26:34,983 DEBUG: View 3 : 0.545023696682
+2016-08-24 15:26:36,583 DEBUG: Best view : Clinic_
+2016-08-24 15:27:20,428 DEBUG: 5.96559463999e-05 proche de zero ?
+2016-08-24 15:27:20,428 DEBUG: Start: Iteration 546
+2016-08-24 15:27:20,453 DEBUG: View 0 : 0.545023696682
+2016-08-24 15:27:20,464 DEBUG: View 1 : 0.488151658768
+2016-08-24 15:27:20,609 DEBUG: View 2 : 0.592417061611
+2016-08-24 15:27:20,621 DEBUG: View 3 : 0.663507109005
+2016-08-24 15:27:22,232 DEBUG: Best view : Clinic_
+2016-08-24 15:28:06,308 DEBUG: 5.95552194623e-05 proche de zero ?
+2016-08-24 15:28:06,309 DEBUG: Start: Iteration 547
+2016-08-24 15:28:06,335 DEBUG: View 0 : 0.488151658768
+2016-08-24 15:28:06,346 DEBUG: View 1 : 0.796208530806
+2016-08-24 15:28:06,484 DEBUG: View 2 : 0.54028436019
+2016-08-24 15:28:06,496 DEBUG: View 3 : 0.582938388626
+2016-08-24 15:28:08,119 DEBUG: Best view : MiRNA__
+2016-08-24 15:28:52,144 DEBUG: 5.94546838169e-05 proche de zero ?
+2016-08-24 15:28:52,144 DEBUG: Start: Iteration 548
+2016-08-24 15:28:52,168 DEBUG: View 0 : 0.483412322275
+2016-08-24 15:28:52,178 DEBUG: View 1 : 0.521327014218
+2016-08-24 15:28:52,310 DEBUG: View 2 : 0.530805687204
+2016-08-24 15:28:52,322 DEBUG: View 3 : 0.582938388626
+2016-08-24 15:28:53,922 DEBUG: Best view : Clinic_
+2016-08-24 15:29:38,112 DEBUG: 5.93543396871e-05 proche de zero ?
+2016-08-24 15:29:38,113 DEBUG: Start: Iteration 549
+2016-08-24 15:29:38,139 DEBUG: View 0 : 0.549763033175
+2016-08-24 15:29:38,152 DEBUG: View 1 : 0.649289099526
+2016-08-24 15:29:38,291 DEBUG: View 2 : 0.568720379147
+2016-08-24 15:29:38,303 DEBUG: View 3 : 0.511848341232
+2016-08-24 15:29:39,936 DEBUG: Best view : MiRNA__
+2016-08-24 15:30:24,016 DEBUG: 5.92541872847e-05 proche de zero ?
+2016-08-24 15:30:24,016 DEBUG: Start: Iteration 550
+2016-08-24 15:30:24,039 DEBUG: View 0 : 0.57345971564
+2016-08-24 15:30:24,049 DEBUG: View 1 : 0.578199052133
+2016-08-24 15:30:24,182 DEBUG: View 2 : 0.60663507109
+2016-08-24 15:30:24,193 DEBUG: View 3 : 0.578199052133
+2016-08-24 15:30:25,802 DEBUG: Best view : RANSeq_
+2016-08-24 15:31:09,943 DEBUG: 5.91542268102e-05 proche de zero ?
+2016-08-24 15:31:09,944 DEBUG: Start: Iteration 551
+2016-08-24 15:31:09,968 DEBUG: View 0 : 0.630331753555
+2016-08-24 15:31:09,979 DEBUG: View 1 : 0.654028436019
+2016-08-24 15:31:10,127 DEBUG: View 2 : 0.649289099526
+2016-08-24 15:31:10,136 DEBUG: View 3 : 0.630331753555
+2016-08-24 15:31:11,803 DEBUG: Best view : RANSeq_
+2016-08-24 15:31:56,974 DEBUG: 5.90544584529e-05 proche de zero ?
+2016-08-24 15:31:56,974 DEBUG: Start: Iteration 552
+2016-08-24 15:31:56,998 DEBUG: View 0 : 0.530805687204
+2016-08-24 15:31:57,009 DEBUG: View 1 : 0.616113744076
+2016-08-24 15:31:57,162 DEBUG: View 2 : 0.54028436019
+2016-08-24 15:31:57,173 DEBUG: View 3 : 0.587677725118
+2016-08-24 15:31:58,845 DEBUG: Best view : MiRNA__
+2016-08-24 15:32:45,571 DEBUG: 5.89548823909e-05 proche de zero ?
+2016-08-24 15:32:45,571 DEBUG: Start: Iteration 553
+2016-08-24 15:32:45,595 DEBUG: View 0 : 0.554502369668
+2016-08-24 15:32:45,605 DEBUG: View 1 : 0.398104265403
+2016-08-24 15:32:45,762 DEBUG: View 2 : 0.559241706161
+2016-08-24 15:32:45,772 DEBUG: View 3 : 0.478672985782
+2016-08-24 15:32:47,481 DEBUG: Best view : RANSeq_
+2016-08-24 15:33:33,740 DEBUG: 5.88554987916e-05 proche de zero ?
+2016-08-24 15:33:33,740 DEBUG: Start: Iteration 554
+2016-08-24 15:33:33,764 DEBUG: View 0 : 0.478672985782
+2016-08-24 15:33:33,775 DEBUG: View 1 : 0.516587677725
+2016-08-24 15:33:33,902 DEBUG: View 2 : 0.545023696682
+2016-08-24 15:33:33,912 DEBUG: View 3 : 0.620853080569
+2016-08-24 15:33:35,669 DEBUG: Best view : Clinic_
+2016-08-24 15:34:20,273 DEBUG: 5.8756307812e-05 proche de zero ?
+2016-08-24 15:34:20,273 DEBUG: Start: Iteration 555
+2016-08-24 15:34:20,299 DEBUG: View 0 : 0.554502369668
+2016-08-24 15:34:20,310 DEBUG: View 1 : 0.597156398104
+2016-08-24 15:34:20,438 DEBUG: View 2 : 0.587677725118
+2016-08-24 15:34:20,447 DEBUG: View 3 : 0.630331753555
+2016-08-24 15:34:22,103 DEBUG: Best view : Clinic_
+2016-08-24 15:35:07,929 DEBUG: 5.86573095984e-05 proche de zero ?
+2016-08-24 15:35:07,930 DEBUG: Start: Iteration 556
+2016-08-24 15:35:07,955 DEBUG: View 0 : 0.592417061611
+2016-08-24 15:35:07,967 DEBUG: View 1 : 0.663507109005
+2016-08-24 15:35:08,095 DEBUG: View 2 : 0.616113744076
+2016-08-24 15:35:08,104 DEBUG: View 3 : 0.549763033175
+2016-08-24 15:35:09,807 DEBUG: Best view : MiRNA__
+2016-08-24 15:35:58,044 DEBUG: 5.85585042868e-05 proche de zero ?
+2016-08-24 15:35:58,044 DEBUG: Start: Iteration 557
+2016-08-24 15:35:58,069 DEBUG: View 0 : 0.535545023697
+2016-08-24 15:35:58,080 DEBUG: View 1 : 0.710900473934
+2016-08-24 15:35:58,243 DEBUG: View 2 : 0.597156398104
+2016-08-24 15:35:58,254 DEBUG: View 3 : 0.57345971564
+2016-08-24 15:36:00,159 DEBUG: Best view : MiRNA__
+2016-08-24 15:36:52,201 DEBUG: 5.84598920032e-05 proche de zero ?
+2016-08-24 15:36:52,327 DEBUG: Start: Iteration 558
+2016-08-24 15:36:54,210 DEBUG: View 0 : 0.559241706161
+2016-08-24 15:36:54,232 DEBUG: View 1 : 0.350710900474
+2016-08-24 15:36:55,005 DEBUG: View 2 : 0.587677725118
+2016-08-24 15:36:56,248 DEBUG: View 3 : 0.601895734597
+2016-08-24 15:36:58,070 DEBUG: Best view : Clinic_
+2016-08-24 15:37:46,240 DEBUG: 5.83614728638e-05 proche de zero ?
+2016-08-24 15:37:46,240 DEBUG: Start: Iteration 559
+2016-08-24 15:37:46,265 DEBUG: View 0 : 0.388625592417
+2016-08-24 15:37:46,276 DEBUG: View 1 : 0.563981042654
+2016-08-24 15:37:46,403 DEBUG: View 2 : 0.521327014218
+2016-08-24 15:37:46,412 DEBUG: View 3 : 0.568720379147
+2016-08-24 15:37:48,074 DEBUG: Best view : Clinic_
+2016-08-24 15:38:34,352 DEBUG: 5.82632469748e-05 proche de zero ?
+2016-08-24 15:38:34,352 DEBUG: Start: Iteration 560
+2016-08-24 15:38:34,389 DEBUG: View 0 : 0.530805687204
+2016-08-24 15:38:34,402 DEBUG: View 1 : 0.592417061611
+2016-08-24 15:38:34,530 DEBUG: View 2 : 0.483412322275
+2016-08-24 15:38:34,540 DEBUG: View 3 : 0.568720379147
+2016-08-24 15:38:36,229 DEBUG: Best view : MiRNA__
+2016-08-24 15:39:22,206 DEBUG: 5.81652144331e-05 proche de zero ?
+2016-08-24 15:39:22,206 DEBUG: Start: Iteration 561
+2016-08-24 15:39:22,229 DEBUG: View 0 : 0.469194312796
+2016-08-24 15:39:22,239 DEBUG: View 1 : 0.706161137441
+2016-08-24 15:39:22,360 DEBUG: View 2 : 0.497630331754
+2016-08-24 15:39:22,369 DEBUG: View 3 : 0.502369668246
+2016-08-24 15:39:24,075 DEBUG: Best view : MiRNA__
+2016-08-24 15:40:10,837 DEBUG: 5.80673753259e-05 proche de zero ?
+2016-08-24 15:40:10,837 DEBUG: Start: Iteration 562
+2016-08-24 15:40:10,859 DEBUG: View 0 : 0.492890995261
+2016-08-24 15:40:10,869 DEBUG: View 1 : 0.668246445498
+2016-08-24 15:40:10,987 DEBUG: View 2 : 0.492890995261
+2016-08-24 15:40:10,997 DEBUG: View 3 : 0.516587677725
+2016-08-24 15:40:12,696 DEBUG: Best view : MiRNA__
+2016-08-24 15:40:59,048 DEBUG: 5.79697297312e-05 proche de zero ?
+2016-08-24 15:40:59,048 DEBUG: Start: Iteration 563
+2016-08-24 15:40:59,071 DEBUG: View 0 : 0.526066350711
+2016-08-24 15:40:59,081 DEBUG: View 1 : 0.582938388626
+2016-08-24 15:40:59,203 DEBUG: View 2 : 0.559241706161
+2016-08-24 15:40:59,212 DEBUG: View 3 : 0.483412322275
+2016-08-24 15:41:00,908 DEBUG: Best view : RANSeq_
+2016-08-24 15:41:47,728 DEBUG: 5.78722777182e-05 proche de zero ?
+2016-08-24 15:41:47,728 DEBUG: Start: Iteration 564
+2016-08-24 15:41:47,751 DEBUG: View 0 : 0.611374407583
+2016-08-24 15:41:47,760 DEBUG: View 1 : 0.75355450237
+2016-08-24 15:41:47,883 DEBUG: View 2 : 0.57345971564
+2016-08-24 15:41:47,893 DEBUG: View 3 : 0.616113744076
+2016-08-24 15:41:49,554 DEBUG: Best view : MiRNA__
+2016-08-24 15:42:36,097 DEBUG: 5.77750193467e-05 proche de zero ?
+2016-08-24 15:42:36,097 DEBUG: Start: Iteration 565
+2016-08-24 15:42:36,119 DEBUG: View 0 : 0.635071090047
+2016-08-24 15:42:36,129 DEBUG: View 1 : 0.554502369668
+2016-08-24 15:42:36,252 DEBUG: View 2 : 0.549763033175
+2016-08-24 15:42:36,262 DEBUG: View 3 : 0.492890995261
+2016-08-24 15:42:37,977 DEBUG: Best view : Methyl_
+2016-08-24 15:43:24,037 DEBUG: 5.76779546681e-05 proche de zero ?
+2016-08-24 15:43:24,037 DEBUG: Start: Iteration 566
+2016-08-24 15:43:24,061 DEBUG: View 0 : 0.635071090047
+2016-08-24 15:43:24,072 DEBUG: View 1 : 0.654028436019
+2016-08-24 15:43:24,198 DEBUG: View 2 : 0.592417061611
+2016-08-24 15:43:24,208 DEBUG: View 3 : 0.592417061611
+2016-08-24 15:43:25,937 DEBUG: Best view : MiRNA__
+2016-08-24 15:44:11,585 DEBUG: 5.75810837249e-05 proche de zero ?
+2016-08-24 15:44:11,585 DEBUG: Start: Iteration 567
+2016-08-24 15:44:11,607 DEBUG: View 0 : 0.582938388626
+2016-08-24 15:44:11,617 DEBUG: View 1 : 0.578199052133
+2016-08-24 15:44:11,732 DEBUG: View 2 : 0.601895734597
+2016-08-24 15:44:11,741 DEBUG: View 3 : 0.582938388626
+2016-08-24 15:44:13,424 DEBUG: Best view : RANSeq_
+2016-08-24 15:45:00,021 DEBUG: 5.74844065512e-05 proche de zero ?
+2016-08-24 15:45:00,022 DEBUG: Start: Iteration 568
+2016-08-24 15:45:00,044 DEBUG: View 0 : 0.440758293839
+2016-08-24 15:45:00,054 DEBUG: View 1 : 0.473933649289
+2016-08-24 15:45:00,181 DEBUG: View 2 : 0.488151658768
+2016-08-24 15:45:00,191 DEBUG: View 3 : 0.578199052133
+2016-08-24 15:45:01,914 DEBUG: Best view : Clinic_
+2016-08-24 15:45:48,690 DEBUG: 5.73879231729e-05 proche de zero ?
+2016-08-24 15:45:48,690 DEBUG: Start: Iteration 569
+2016-08-24 15:45:48,713 DEBUG: View 0 : 0.663507109005
+2016-08-24 15:45:48,723 DEBUG: View 1 : 0.383886255924
+2016-08-24 15:45:48,840 DEBUG: View 2 : 0.592417061611
+2016-08-24 15:45:48,849 DEBUG: View 3 : 0.635071090047
+2016-08-24 15:45:50,539 DEBUG: Best view : Methyl_
+2016-08-24 15:46:37,307 DEBUG: 5.72916336075e-05 proche de zero ?
+2016-08-24 15:46:37,308 DEBUG: Start: Iteration 570
+2016-08-24 15:46:37,332 DEBUG: View 0 : 0.630331753555
+2016-08-24 15:46:37,347 DEBUG: View 1 : 0.630331753555
+2016-08-24 15:46:37,468 DEBUG: View 2 : 0.60663507109
+2016-08-24 15:46:37,479 DEBUG: View 3 : 0.592417061611
+2016-08-24 15:46:39,281 DEBUG: Best view : Methyl_
+2016-08-24 15:47:25,307 DEBUG: 5.71955378646e-05 proche de zero ?
+2016-08-24 15:47:25,308 DEBUG: Start: Iteration 571
+2016-08-24 15:47:25,331 DEBUG: View 0 : 0.763033175355
+2016-08-24 15:47:25,341 DEBUG: View 1 : 0.682464454976
+2016-08-24 15:47:25,471 DEBUG: View 2 : 0.554502369668
+2016-08-24 15:47:25,481 DEBUG: View 3 : 0.563981042654
+2016-08-24 15:47:27,250 DEBUG: Best view : Methyl_
+2016-08-24 15:48:14,586 DEBUG: 5.70996359457e-05 proche de zero ?
+2016-08-24 15:48:14,586 DEBUG: Start: Iteration 572
+2016-08-24 15:48:14,607 DEBUG: View 0 : 0.635071090047
+2016-08-24 15:48:14,619 DEBUG: View 1 : 0.39336492891
+2016-08-24 15:48:14,737 DEBUG: View 2 : 0.559241706161
+2016-08-24 15:48:14,747 DEBUG: View 3 : 0.649289099526
+2016-08-24 15:48:16,681 DEBUG: Best view : Clinic_
+2016-08-24 15:49:05,561 DEBUG: 5.70039278448e-05 proche de zero ?
+2016-08-24 15:49:05,561 DEBUG: Start: Iteration 573
+2016-08-24 15:49:05,583 DEBUG: View 0 : 0.725118483412
+2016-08-24 15:49:05,593 DEBUG: View 1 : 0.516587677725
+2016-08-24 15:49:05,714 DEBUG: View 2 : 0.597156398104
+2016-08-24 15:49:05,723 DEBUG: View 3 : 0.649289099526
+2016-08-24 15:49:07,444 DEBUG: Best view : Methyl_
+2016-08-24 15:49:54,785 DEBUG: 5.69084135481e-05 proche de zero ?
+2016-08-24 15:49:54,785 DEBUG: Start: Iteration 574
+2016-08-24 15:49:54,807 DEBUG: View 0 : 0.521327014218
+2016-08-24 15:49:54,817 DEBUG: View 1 : 0.729857819905
+2016-08-24 15:49:54,937 DEBUG: View 2 : 0.592417061611
+2016-08-24 15:49:54,946 DEBUG: View 3 : 0.668246445498
+2016-08-24 15:49:56,655 DEBUG: Best view : MiRNA__
+2016-08-24 15:50:45,854 DEBUG: 5.68130930342e-05 proche de zero ?
+2016-08-24 15:50:45,854 DEBUG: Start: Iteration 575
+2016-08-24 15:50:45,876 DEBUG: View 0 : 0.398104265403
+2016-08-24 15:50:45,885 DEBUG: View 1 : 0.668246445498
+2016-08-24 15:50:46,010 DEBUG: View 2 : 0.57345971564
+2016-08-24 15:50:46,020 DEBUG: View 3 : 0.592417061611
+2016-08-24 15:50:47,761 DEBUG: Best view : MiRNA__
+2016-08-24 15:51:34,498 DEBUG: 5.67280869189e-05 proche de zero ?
+2016-08-24 15:51:34,498 DEBUG: Start: Iteration 576
+2016-08-24 15:51:34,520 DEBUG: View 0 : 0.582938388626
+2016-08-24 15:51:34,531 DEBUG: View 1 : 0.616113744076
+2016-08-24 15:51:34,650 DEBUG: View 2 : 0.582938388626
+2016-08-24 15:51:34,659 DEBUG: View 3 : 0.436018957346
+2016-08-24 15:51:36,373 DEBUG: Best view : MiRNA__
+2016-08-24 15:52:24,031 DEBUG: 5.6643196095e-05 proche de zero ?
+2016-08-24 15:52:24,031 DEBUG: Start: Iteration 577
+2016-08-24 15:52:24,053 DEBUG: View 0 : 0.473933649289
+2016-08-24 15:52:24,062 DEBUG: View 1 : 0.421800947867
+2016-08-24 15:52:24,187 DEBUG: View 2 : 0.578199052133
+2016-08-24 15:52:24,196 DEBUG: View 3 : 0.611374407583
+2016-08-24 15:52:25,951 DEBUG: Best view : Clinic_
+2016-08-24 15:53:13,077 DEBUG: 5.65584211559e-05 proche de zero ?
+2016-08-24 15:53:13,077 DEBUG: Start: Iteration 578
+2016-08-24 15:53:13,100 DEBUG: View 0 : 0.374407582938
+2016-08-24 15:53:13,111 DEBUG: View 1 : 0.658767772512
+2016-08-24 15:53:13,256 DEBUG: View 2 : 0.511848341232
+2016-08-24 15:53:13,267 DEBUG: View 3 : 0.654028436019
+2016-08-24 15:53:15,260 DEBUG: Best view : Clinic_
+2016-08-24 15:54:03,129 DEBUG: 5.64637334828e-05 proche de zero ?
+2016-08-24 15:54:03,129 DEBUG: Start: Iteration 579
+2016-08-24 15:54:03,154 DEBUG: View 0 : 0.554502369668
+2016-08-24 15:54:03,164 DEBUG: View 1 : 0.554502369668
+2016-08-24 15:54:03,304 DEBUG: View 2 : 0.601895734597
+2016-08-24 15:54:03,313 DEBUG: View 3 : 0.644549763033
+2016-08-24 15:54:05,055 DEBUG: Best view : Clinic_
+2016-08-24 15:54:52,005 DEBUG: 5.63792391847e-05 proche de zero ?
+2016-08-24 15:54:52,005 DEBUG: Start: Iteration 580
+2016-08-24 15:54:52,027 DEBUG: View 0 : 0.563981042654
+2016-08-24 15:54:52,036 DEBUG: View 1 : 0.388625592417
+2016-08-24 15:54:52,159 DEBUG: View 2 : 0.635071090047
+2016-08-24 15:54:52,168 DEBUG: View 3 : 0.568720379147
+2016-08-24 15:54:53,905 DEBUG: Best view : RANSeq_
+2016-08-24 15:55:42,320 DEBUG: 5.6284893273e-05 proche de zero ?
+2016-08-24 15:55:42,320 DEBUG: Start: Iteration 581
+2016-08-24 15:55:42,359 DEBUG: View 0 : 0.60663507109
+2016-08-24 15:55:42,377 DEBUG: View 1 : 0.658767772512
+2016-08-24 15:55:42,540 DEBUG: View 2 : 0.563981042654
+2016-08-24 15:55:42,549 DEBUG: View 3 : 0.54028436019
+2016-08-24 15:55:44,296 DEBUG: Best view : MiRNA__
+2016-08-24 15:56:32,161 DEBUG: 5.61907418602e-05 proche de zero ?
+2016-08-24 15:56:32,161 DEBUG: Start: Iteration 582
+2016-08-24 15:56:32,183 DEBUG: View 0 : 0.625592417062
+2016-08-24 15:56:32,193 DEBUG: View 1 : 0.483412322275
+2016-08-24 15:56:32,312 DEBUG: View 2 : 0.57345971564
+2016-08-24 15:56:32,321 DEBUG: View 3 : 0.630331753555
+2016-08-24 15:56:34,074 DEBUG: Best view : Clinic_
+2016-08-24 15:57:22,663 DEBUG: 5.60967848622e-05 proche de zero ?
+2016-08-24 15:57:22,663 DEBUG: Start: Iteration 583
+2016-08-24 15:57:22,698 DEBUG: View 0 : 0.625592417062
+2016-08-24 15:57:22,710 DEBUG: View 1 : 0.507109004739
+2016-08-24 15:57:22,848 DEBUG: View 2 : 0.545023696682
+2016-08-24 15:57:22,859 DEBUG: View 3 : 0.597156398104
+2016-08-24 15:57:24,791 DEBUG: Best view : Methyl_
+2016-08-24 15:58:13,942 DEBUG: 5.60030221883e-05 proche de zero ?
+2016-08-24 15:58:13,943 DEBUG: Start: Iteration 584
+2016-08-24 15:58:13,965 DEBUG: View 0 : 0.587677725118
+2016-08-24 15:58:13,976 DEBUG: View 1 : 0.663507109005
+2016-08-24 15:58:14,103 DEBUG: View 2 : 0.601895734597
+2016-08-24 15:58:14,113 DEBUG: View 3 : 0.559241706161
+2016-08-24 15:58:15,877 DEBUG: Best view : MiRNA__
+2016-08-24 15:59:04,748 DEBUG: 5.59094537419e-05 proche de zero ?
+2016-08-24 15:59:04,749 DEBUG: Start: Iteration 585
+2016-08-24 15:59:04,770 DEBUG: View 0 : 0.601895734597
+2016-08-24 15:59:04,780 DEBUG: View 1 : 0.516587677725
+2016-08-24 15:59:04,901 DEBUG: View 2 : 0.483412322275
+2016-08-24 15:59:04,910 DEBUG: View 3 : 0.563981042654
+2016-08-24 15:59:06,785 DEBUG: Best view : Methyl_
+2016-08-24 15:59:54,484 DEBUG: 5.58160794201e-05 proche de zero ?
+2016-08-24 15:59:54,484 DEBUG: Start: Iteration 586
+2016-08-24 15:59:54,506 DEBUG: View 0 : 0.568720379147
+2016-08-24 15:59:54,516 DEBUG: View 1 : 0.535545023697
+2016-08-24 15:59:54,633 DEBUG: View 2 : 0.568720379147
+2016-08-24 15:59:54,642 DEBUG: View 3 : 0.706161137441
+2016-08-24 15:59:56,355 DEBUG: Best view : Clinic_
+2016-08-24 16:00:44,580 DEBUG: 5.5722899114e-05 proche de zero ?
+2016-08-24 16:00:44,580 DEBUG: Start: Iteration 587
+2016-08-24 16:00:44,602 DEBUG: View 0 : 0.668246445498
+2016-08-24 16:00:44,612 DEBUG: View 1 : 0.649289099526
+2016-08-24 16:00:44,734 DEBUG: View 2 : 0.507109004739
+2016-08-24 16:00:44,743 DEBUG: View 3 : 0.57345971564
+2016-08-24 16:00:46,475 DEBUG: Best view : Methyl_
+2016-08-24 16:01:33,775 DEBUG: 5.5639675002e-05 proche de zero ?
+2016-08-24 16:01:33,775 DEBUG: Start: Iteration 588
+2016-08-24 16:01:33,797 DEBUG: View 0 : 0.526066350711
+2016-08-24 16:01:33,807 DEBUG: View 1 : 0.625592417062
+2016-08-24 16:01:33,931 DEBUG: View 2 : 0.582938388626
+2016-08-24 16:01:33,941 DEBUG: View 3 : 0.60663507109
+2016-08-24 16:01:35,687 DEBUG: Best view : MiRNA__
+2016-08-24 16:02:23,165 DEBUG: 5.55565704549e-05 proche de zero ?
+2016-08-24 16:02:23,165 DEBUG: Start: Iteration 589
+2016-08-24 16:02:23,187 DEBUG: View 0 : 0.568720379147
+2016-08-24 16:02:23,196 DEBUG: View 1 : 0.668246445498
+2016-08-24 16:02:23,317 DEBUG: View 2 : 0.635071090047
+2016-08-24 16:02:23,326 DEBUG: View 3 : 0.54028436019
+2016-08-24 16:02:25,045 DEBUG: Best view : MiRNA__
+2016-08-24 16:03:12,485 DEBUG: 5.54735859372e-05 proche de zero ?
+2016-08-24 16:03:12,485 DEBUG: Start: Iteration 590
+2016-08-24 16:03:12,510 DEBUG: View 0 : 0.672985781991
+2016-08-24 16:03:12,521 DEBUG: View 1 : 0.317535545024
+2016-08-24 16:03:12,658 DEBUG: View 2 : 0.516587677725
+2016-08-24 16:03:12,668 DEBUG: View 3 : 0.616113744076
+2016-08-24 16:03:14,546 DEBUG: Best view : Methyl_
+2016-08-24 16:04:01,915 DEBUG: 5.53907219025e-05 proche de zero ?
+2016-08-24 16:04:01,915 DEBUG: Start: Iteration 591
+2016-08-24 16:04:01,937 DEBUG: View 0 : 0.554502369668
+2016-08-24 16:04:01,947 DEBUG: View 1 : 0.450236966825
+2016-08-24 16:04:02,066 DEBUG: View 2 : 0.625592417062
+2016-08-24 16:04:02,075 DEBUG: View 3 : 0.568720379147
+2016-08-24 16:04:03,799 DEBUG: Best view : RANSeq_
+2016-08-24 16:04:50,961 DEBUG: 5.53079787937e-05 proche de zero ?
+2016-08-24 16:04:50,961 DEBUG: Start: Iteration 592
+2016-08-24 16:04:50,983 DEBUG: View 0 : 0.644549763033
+2016-08-24 16:04:50,994 DEBUG: View 1 : 0.734597156398
+2016-08-24 16:04:51,111 DEBUG: View 2 : 0.644549763033
+2016-08-24 16:04:51,120 DEBUG: View 3 : 0.60663507109
+2016-08-24 16:04:52,847 DEBUG: Best view : MiRNA__
+2016-08-24 16:05:40,087 DEBUG: 5.52253570429e-05 proche de zero ?
+2016-08-24 16:05:40,087 DEBUG: Start: Iteration 593
+2016-08-24 16:05:40,109 DEBUG: View 0 : 0.507109004739
+2016-08-24 16:05:40,119 DEBUG: View 1 : 0.701421800948
+2016-08-24 16:05:40,235 DEBUG: View 2 : 0.473933649289
+2016-08-24 16:05:40,245 DEBUG: View 3 : 0.625592417062
+2016-08-24 16:05:41,978 DEBUG: Best view : MiRNA__
+2016-08-24 16:06:29,547 DEBUG: 5.51428570719e-05 proche de zero ?
+2016-08-24 16:06:29,547 DEBUG: Start: Iteration 594
+2016-08-24 16:06:29,569 DEBUG: View 0 : 0.445497630332
+2016-08-24 16:06:29,579 DEBUG: View 1 : 0.355450236967
+2016-08-24 16:06:29,699 DEBUG: View 2 : 0.530805687204
+2016-08-24 16:06:29,708 DEBUG: View 3 : 0.57345971564
+2016-08-24 16:06:31,458 DEBUG: Best view : Clinic_
+2016-08-24 16:07:19,034 DEBUG: 5.5060479292e-05 proche de zero ?
+2016-08-24 16:07:19,034 DEBUG: Start: Iteration 595
+2016-08-24 16:07:19,057 DEBUG: View 0 : 0.563981042654
+2016-08-24 16:07:19,067 DEBUG: View 1 : 0.502369668246
+2016-08-24 16:07:19,187 DEBUG: View 2 : 0.601895734597
+2016-08-24 16:07:19,196 DEBUG: View 3 : 0.658767772512
+2016-08-24 16:07:20,939 DEBUG: Best view : Clinic_
+2016-08-24 16:08:08,827 DEBUG: 5.49782241045e-05 proche de zero ?
+2016-08-24 16:08:08,827 DEBUG: Start: Iteration 596
+2016-08-24 16:08:08,849 DEBUG: View 0 : 0.511848341232
+2016-08-24 16:08:08,859 DEBUG: View 1 : 0.554502369668
+2016-08-24 16:08:08,981 DEBUG: View 2 : 0.60663507109
+2016-08-24 16:08:08,990 DEBUG: View 3 : 0.687203791469
+2016-08-24 16:08:10,760 DEBUG: Best view : Clinic_
+2016-08-24 16:08:58,882 DEBUG: 5.48960919006e-05 proche de zero ?
+2016-08-24 16:08:58,882 DEBUG: Start: Iteration 597
+2016-08-24 16:08:58,913 DEBUG: View 0 : 0.478672985782
+2016-08-24 16:08:58,933 DEBUG: View 1 : 0.696682464455
+2016-08-24 16:08:59,084 DEBUG: View 2 : 0.625592417062
+2016-08-24 16:08:59,095 DEBUG: View 3 : 0.587677725118
+2016-08-24 16:09:00,892 DEBUG: Best view : MiRNA__
+2016-08-24 16:09:49,241 DEBUG: 5.48140830615e-05 proche de zero ?
+2016-08-24 16:09:49,241 DEBUG: Start: Iteration 598
+2016-08-24 16:09:49,263 DEBUG: View 0 : 0.582938388626
+2016-08-24 16:09:49,272 DEBUG: View 1 : 0.616113744076
+2016-08-24 16:09:49,391 DEBUG: View 2 : 0.554502369668
+2016-08-24 16:09:49,400 DEBUG: View 3 : 0.592417061611
+2016-08-24 16:09:51,155 DEBUG: Best view : Clinic_
+2016-08-24 16:10:39,013 DEBUG: 5.47321979589e-05 proche de zero ?
+2016-08-24 16:10:39,013 DEBUG: Start: Iteration 599
+2016-08-24 16:10:39,035 DEBUG: View 0 : 0.592417061611
+2016-08-24 16:10:39,045 DEBUG: View 1 : 0.592417061611
+2016-08-24 16:10:39,166 DEBUG: View 2 : 0.497630331754
+2016-08-24 16:10:39,176 DEBUG: View 3 : 0.578199052133
+2016-08-24 16:10:40,931 DEBUG: Best view : MiRNA__
+2016-08-24 16:11:28,926 DEBUG: 5.46504369546e-05 proche de zero ?
+2016-08-24 16:11:28,926 DEBUG: Start: Iteration 600
+2016-08-24 16:11:28,948 DEBUG: View 0 : 0.431279620853
+2016-08-24 16:11:28,957 DEBUG: View 1 : 0.663507109005
+2016-08-24 16:11:29,078 DEBUG: View 2 : 0.620853080569
+2016-08-24 16:11:29,087 DEBUG: View 3 : 0.616113744076
+2016-08-24 16:11:30,845 DEBUG: Best view : MiRNA__
+2016-08-24 16:12:18,982 DEBUG: 5.45688004013e-05 proche de zero ?
+2016-08-24 16:12:18,983 DEBUG: Start: Iteration 601
+2016-08-24 16:12:19,004 DEBUG: View 0 : 0.345971563981
+2016-08-24 16:12:19,014 DEBUG: View 1 : 0.696682464455
+2016-08-24 16:12:19,131 DEBUG: View 2 : 0.57345971564
+2016-08-24 16:12:19,141 DEBUG: View 3 : 0.620853080569
+2016-08-24 16:12:20,902 DEBUG: Best view : MiRNA__
+2016-08-24 16:13:09,183 DEBUG: 5.4487288642e-05 proche de zero ?
+2016-08-24 16:13:09,183 DEBUG: Start: Iteration 602
+2016-08-24 16:13:09,205 DEBUG: View 0 : 0.545023696682
+2016-08-24 16:13:09,214 DEBUG: View 1 : 0.57345971564
+2016-08-24 16:13:09,342 DEBUG: View 2 : 0.582938388626
+2016-08-24 16:13:09,352 DEBUG: View 3 : 0.582938388626
+2016-08-24 16:13:11,147 DEBUG: Best view : Clinic_
+2016-08-24 16:13:59,514 DEBUG: 5.44059020109e-05 proche de zero ?
+2016-08-24 16:13:59,514 DEBUG: Start: Iteration 603
+2016-08-24 16:13:59,536 DEBUG: View 0 : 0.57345971564
+2016-08-24 16:13:59,545 DEBUG: View 1 : 0.535545023697
+2016-08-24 16:13:59,674 DEBUG: View 2 : 0.559241706161
+2016-08-24 16:13:59,684 DEBUG: View 3 : 0.710900473934
+2016-08-24 16:14:01,459 DEBUG: Best view : Clinic_
+2016-08-24 16:14:49,977 DEBUG: 5.43246408327e-05 proche de zero ?
+2016-08-24 16:14:49,977 DEBUG: Start: Iteration 604
+2016-08-24 16:14:49,999 DEBUG: View 0 : 0.748815165877
+2016-08-24 16:14:50,009 DEBUG: View 1 : 0.691943127962
+2016-08-24 16:14:50,131 DEBUG: View 2 : 0.625592417062
+2016-08-24 16:14:50,140 DEBUG: View 3 : 0.57345971564
+2016-08-24 16:14:51,957 DEBUG: Best view : Methyl_
+2016-08-24 16:15:41,515 DEBUG: 5.42435054237e-05 proche de zero ?
+2016-08-24 16:15:41,515 DEBUG: Start: Iteration 605
+2016-08-24 16:15:41,537 DEBUG: View 0 : 0.421800947867
+2016-08-24 16:15:41,547 DEBUG: View 1 : 0.635071090047
+2016-08-24 16:15:41,663 DEBUG: View 2 : 0.597156398104
+2016-08-24 16:15:41,673 DEBUG: View 3 : 0.54028436019
+2016-08-24 16:15:43,441 DEBUG: Best view : MiRNA__
+2016-08-24 16:16:32,734 DEBUG: 5.41624960909e-05 proche de zero ?
+2016-08-24 16:16:32,734 DEBUG: Start: Iteration 606
+2016-08-24 16:16:32,759 DEBUG: View 0 : 0.601895734597
+2016-08-24 16:16:32,770 DEBUG: View 1 : 0.644549763033
+2016-08-24 16:16:32,925 DEBUG: View 2 : 0.521327014218
+2016-08-24 16:16:32,937 DEBUG: View 3 : 0.582938388626
+2016-08-24 16:16:34,787 DEBUG: Best view : MiRNA__
+2016-08-24 16:17:23,226 DEBUG: 5.4081613133e-05 proche de zero ?
+2016-08-24 16:17:23,226 DEBUG: Start: Iteration 607
+2016-08-24 16:17:23,248 DEBUG: View 0 : 0.630331753555
+2016-08-24 16:17:23,258 DEBUG: View 1 : 0.578199052133
+2016-08-24 16:17:23,376 DEBUG: View 2 : 0.635071090047
+2016-08-24 16:17:23,386 DEBUG: View 3 : 0.668246445498
+2016-08-24 16:17:25,176 DEBUG: Best view : Clinic_
+2016-08-24 16:18:13,881 DEBUG: 5.400085684e-05 proche de zero ?
+2016-08-24 16:18:13,881 DEBUG: Start: Iteration 608
+2016-08-24 16:18:13,903 DEBUG: View 0 : 0.644549763033
+2016-08-24 16:18:13,912 DEBUG: View 1 : 0.355450236967
+2016-08-24 16:18:14,026 DEBUG: View 2 : 0.492890995261
+2016-08-24 16:18:14,036 DEBUG: View 3 : 0.635071090047
+2016-08-24 16:18:15,817 DEBUG: Best view : Clinic_
+2016-08-24 16:19:04,326 DEBUG: 5.39202274935e-05 proche de zero ?
+2016-08-24 16:19:04,327 DEBUG: Start: Iteration 609
+2016-08-24 16:19:04,348 DEBUG: View 0 : 0.473933649289
+2016-08-24 16:19:04,358 DEBUG: View 1 : 0.535545023697
+2016-08-24 16:19:04,480 DEBUG: View 2 : 0.549763033175
+2016-08-24 16:19:04,490 DEBUG: View 3 : 0.672985781991
+2016-08-24 16:19:06,282 DEBUG: Best view : Clinic_
+2016-08-24 16:19:54,903 DEBUG: 5.38397253669e-05 proche de zero ?
+2016-08-24 16:19:54,903 DEBUG: Start: Iteration 610
+2016-08-24 16:19:54,924 DEBUG: View 0 : 0.568720379147
+2016-08-24 16:19:54,934 DEBUG: View 1 : 0.691943127962
+2016-08-24 16:19:55,050 DEBUG: View 2 : 0.554502369668
+2016-08-24 16:19:55,061 DEBUG: View 3 : 0.60663507109
+2016-08-24 16:19:56,858 DEBUG: Best view : MiRNA__
+2016-08-24 16:20:45,411 DEBUG: 5.37593507254e-05 proche de zero ?
+2016-08-24 16:20:45,412 DEBUG: Start: Iteration 611
+2016-08-24 16:20:45,433 DEBUG: View 0 : 0.445497630332
+2016-08-24 16:20:45,443 DEBUG: View 1 : 0.511848341232
+2016-08-24 16:20:45,571 DEBUG: View 2 : 0.497630331754
+2016-08-24 16:20:45,581 DEBUG: View 3 : 0.554502369668
+2016-08-24 16:20:47,384 DEBUG: Best view : Clinic_
+2016-08-24 16:21:36,123 DEBUG: 5.3679103826e-05 proche de zero ?
+2016-08-24 16:21:36,124 DEBUG: Start: Iteration 612
+2016-08-24 16:21:36,145 DEBUG: View 0 : 0.478672985782
+2016-08-24 16:21:36,155 DEBUG: View 1 : 0.630331753555
+2016-08-24 16:21:36,304 DEBUG: View 2 : 0.616113744076
+2016-08-24 16:21:36,313 DEBUG: View 3 : 0.649289099526
+2016-08-24 16:21:38,101 DEBUG: Best view : Clinic_
+2016-08-24 16:22:28,302 DEBUG: 5.3598984918e-05 proche de zero ?
+2016-08-24 16:22:28,302 DEBUG: Start: Iteration 613
+2016-08-24 16:22:28,325 DEBUG: View 0 : 0.488151658768
+2016-08-24 16:22:28,334 DEBUG: View 1 : 0.60663507109
+2016-08-24 16:22:28,475 DEBUG: View 2 : 0.578199052133
+2016-08-24 16:22:28,485 DEBUG: View 3 : 0.587677725118
+2016-08-24 16:22:30,299 DEBUG: Best view : MiRNA__
+2016-08-24 16:23:19,384 DEBUG: 5.35189942428e-05 proche de zero ?
+2016-08-24 16:23:19,384 DEBUG: Start: Iteration 614
+2016-08-24 16:23:19,406 DEBUG: View 0 : 0.654028436019
+2016-08-24 16:23:19,415 DEBUG: View 1 : 0.60663507109
+2016-08-24 16:23:19,552 DEBUG: View 2 : 0.554502369668
+2016-08-24 16:23:19,564 DEBUG: View 3 : 0.60663507109
+2016-08-24 16:23:21,373 DEBUG: Best view : Methyl_
+2016-08-24 16:24:10,622 DEBUG: 5.3439132034e-05 proche de zero ?
+2016-08-24 16:24:10,622 DEBUG: Start: Iteration 615
+2016-08-24 16:24:10,645 DEBUG: View 0 : 0.559241706161
+2016-08-24 16:24:10,655 DEBUG: View 1 : 0.658767772512
+2016-08-24 16:24:10,783 DEBUG: View 2 : 0.559241706161
+2016-08-24 16:24:10,794 DEBUG: View 3 : 0.601895734597
+2016-08-24 16:24:12,596 DEBUG: Best view : MiRNA__
+2016-08-24 16:25:01,702 DEBUG: 5.33593985177e-05 proche de zero ?
+2016-08-24 16:25:01,703 DEBUG: Start: Iteration 616
+2016-08-24 16:25:01,725 DEBUG: View 0 : 0.63981042654
+2016-08-24 16:25:01,736 DEBUG: View 1 : 0.488151658768
+2016-08-24 16:25:01,866 DEBUG: View 2 : 0.587677725118
+2016-08-24 16:25:01,878 DEBUG: View 3 : 0.568720379147
+2016-08-24 16:25:03,674 DEBUG: Best view : Methyl_
+2016-08-24 16:25:53,123 DEBUG: 5.32797939126e-05 proche de zero ?
+2016-08-24 16:25:53,123 DEBUG: Start: Iteration 617
+2016-08-24 16:25:53,145 DEBUG: View 0 : 0.796208530806
+2016-08-24 16:25:53,156 DEBUG: View 1 : 0.630331753555
+2016-08-24 16:25:53,292 DEBUG: View 2 : 0.554502369668
+2016-08-24 16:25:53,304 DEBUG: View 3 : 0.545023696682
+2016-08-24 16:25:55,142 DEBUG: Best view : Methyl_
+2016-08-24 16:26:44,515 DEBUG: 5.32092650058e-05 proche de zero ?
+2016-08-24 16:26:44,515 DEBUG: Start: Iteration 618
+2016-08-24 16:26:44,537 DEBUG: View 0 : 0.587677725118
+2016-08-24 16:26:44,549 DEBUG: View 1 : 0.635071090047
+2016-08-24 16:26:44,686 DEBUG: View 2 : 0.473933649289
+2016-08-24 16:26:44,697 DEBUG: View 3 : 0.57345971564
+2016-08-24 16:26:46,509 DEBUG: Best view : MiRNA__
+2016-08-24 16:27:36,201 DEBUG: 5.31298792906e-05 proche de zero ?
+2016-08-24 16:27:36,201 DEBUG: Start: Iteration 619
+2016-08-24 16:27:36,225 DEBUG: View 0 : 0.563981042654
+2016-08-24 16:27:36,235 DEBUG: View 1 : 0.649289099526
+2016-08-24 16:27:36,365 DEBUG: View 2 : 0.563981042654
+2016-08-24 16:27:36,376 DEBUG: View 3 : 0.57345971564
+2016-08-24 16:27:38,191 DEBUG: Best view : MiRNA__
+2016-08-24 16:28:27,719 DEBUG: 5.30506233104e-05 proche de zero ?
+2016-08-24 16:28:27,719 DEBUG: Start: Iteration 620
+2016-08-24 16:28:27,741 DEBUG: View 0 : 0.497630331754
+2016-08-24 16:28:27,753 DEBUG: View 1 : 0.800947867299
+2016-08-24 16:28:27,886 DEBUG: View 2 : 0.559241706161
+2016-08-24 16:28:27,896 DEBUG: View 3 : 0.597156398104
+2016-08-24 16:28:29,803 DEBUG: Best view : MiRNA__
+2016-08-24 16:29:19,334 DEBUG: 5.29803680113e-05 proche de zero ?
+2016-08-24 16:29:19,335 DEBUG: Start: Iteration 621
+2016-08-24 16:29:24,389 DEBUG: View 0 : 0.587677725118
+2016-08-24 16:29:24,398 DEBUG: View 1 : 0.691943127962
+2016-08-24 16:29:24,532 DEBUG: View 2 : 0.545023696682
+2016-08-24 16:29:24,541 DEBUG: View 3 : 0.473933649289
+2016-08-24 16:29:26,362 DEBUG: Best view : MiRNA__
+2016-08-24 16:30:16,056 DEBUG: 5.29013330137e-05 proche de zero ?
+2016-08-24 16:30:16,056 DEBUG: Start: Iteration 622
+2016-08-24 16:30:16,078 DEBUG: View 0 : 0.473933649289
+2016-08-24 16:30:16,088 DEBUG: View 1 : 0.530805687204
+2016-08-24 16:30:16,232 DEBUG: View 2 : 0.587677725118
+2016-08-24 16:30:16,244 DEBUG: View 3 : 0.587677725118
+2016-08-24 16:30:18,066 DEBUG: Best view : Clinic_
+2016-08-24 16:31:08,022 DEBUG: 5.28224285036e-05 proche de zero ?
+2016-08-24 16:31:08,022 DEBUG: Start: Iteration 623
+2016-08-24 16:31:08,045 DEBUG: View 0 : 0.625592417062
+2016-08-24 16:31:08,055 DEBUG: View 1 : 0.57345971564
+2016-08-24 16:31:08,186 DEBUG: View 2 : 0.563981042654
+2016-08-24 16:31:08,197 DEBUG: View 3 : 0.492890995261
+2016-08-24 16:31:10,022 DEBUG: Best view : Methyl_
+2016-08-24 16:31:59,790 DEBUG: 5.27436546477e-05 proche de zero ?
+2016-08-24 16:31:59,790 DEBUG: Start: Iteration 624
+2016-08-24 16:31:59,813 DEBUG: View 0 : 0.625592417062
+2016-08-24 16:31:59,824 DEBUG: View 1 : 0.492890995261
+2016-08-24 16:31:59,961 DEBUG: View 2 : 0.502369668246
+2016-08-24 16:31:59,973 DEBUG: View 3 : 0.592417061611
+2016-08-24 16:32:01,813 DEBUG: Best view : Clinic_
+2016-08-24 16:32:51,910 DEBUG: 5.26650116059e-05 proche de zero ?
+2016-08-24 16:32:51,910 DEBUG: Start: Iteration 625
+2016-08-24 16:32:51,932 DEBUG: View 0 : 0.521327014218
+2016-08-24 16:32:51,942 DEBUG: View 1 : 0.57345971564
+2016-08-24 16:32:52,076 DEBUG: View 2 : 0.597156398104
+2016-08-24 16:32:52,088 DEBUG: View 3 : 0.511848341232
+2016-08-24 16:32:53,919 DEBUG: Best view : MiRNA__
+2016-08-24 16:33:43,825 DEBUG: 5.25864995314e-05 proche de zero ?
+2016-08-24 16:33:43,825 DEBUG: Start: Iteration 626
+2016-08-24 16:33:43,846 DEBUG: View 0 : 0.464454976303
+2016-08-24 16:33:43,856 DEBUG: View 1 : 0.687203791469
+2016-08-24 16:33:43,984 DEBUG: View 2 : 0.469194312796
+2016-08-24 16:33:43,996 DEBUG: View 3 : 0.592417061611
+2016-08-24 16:33:45,827 DEBUG: Best view : MiRNA__
+2016-08-24 16:34:35,741 DEBUG: 5.25081185713e-05 proche de zero ?
+2016-08-24 16:34:35,741 DEBUG: Start: Iteration 627
+2016-08-24 16:34:35,763 DEBUG: View 0 : 0.559241706161
+2016-08-24 16:34:35,773 DEBUG: View 1 : 0.672985781991
+2016-08-24 16:34:35,904 DEBUG: View 2 : 0.530805687204
+2016-08-24 16:34:35,915 DEBUG: View 3 : 0.630331753555
+2016-08-24 16:34:37,740 DEBUG: Best view : MiRNA__
+2016-08-24 16:35:27,702 DEBUG: 5.24298688663e-05 proche de zero ?
+2016-08-24 16:35:27,702 DEBUG: Start: Iteration 628
+2016-08-24 16:35:27,724 DEBUG: View 0 : 0.563981042654
+2016-08-24 16:35:27,734 DEBUG: View 1 : 0.663507109005
+2016-08-24 16:35:27,869 DEBUG: View 2 : 0.587677725118
+2016-08-24 16:35:27,881 DEBUG: View 3 : 0.521327014218
+2016-08-24 16:35:29,718 DEBUG: Best view : MiRNA__
+2016-08-24 16:36:20,008 DEBUG: 5.23517505506e-05 proche de zero ?
+2016-08-24 16:36:20,008 DEBUG: Start: Iteration 629
+2016-08-24 16:36:20,030 DEBUG: View 0 : 0.654028436019
+2016-08-24 16:36:20,040 DEBUG: View 1 : 0.649289099526
+2016-08-24 16:36:20,164 DEBUG: View 2 : 0.497630331754
+2016-08-24 16:36:20,176 DEBUG: View 3 : 0.60663507109
+2016-08-24 16:36:22,019 DEBUG: Best view : Methyl_
+2016-08-24 16:37:13,881 DEBUG: 5.22737637527e-05 proche de zero ?
+2016-08-24 16:37:13,882 DEBUG: Start: Iteration 630
+2016-08-24 16:37:13,903 DEBUG: View 0 : 0.649289099526
+2016-08-24 16:37:13,913 DEBUG: View 1 : 0.672985781991
+2016-08-24 16:37:14,046 DEBUG: View 2 : 0.545023696682
+2016-08-24 16:37:14,058 DEBUG: View 3 : 0.549763033175
+2016-08-24 16:37:16,082 DEBUG: Best view : MiRNA__
+2016-08-24 16:38:06,920 DEBUG: 5.21959085947e-05 proche de zero ?
+2016-08-24 16:38:06,921 DEBUG: Start: Iteration 631
+2016-08-24 16:38:06,943 DEBUG: View 0 : 0.54028436019
+2016-08-24 16:38:06,953 DEBUG: View 1 : 0.57345971564
+2016-08-24 16:38:07,079 DEBUG: View 2 : 0.616113744076
+2016-08-24 16:38:07,090 DEBUG: View 3 : 0.563981042654
+2016-08-24 16:38:08,965 DEBUG: Best view : RANSeq_
+2016-08-24 16:38:59,459 DEBUG: 5.21181851928e-05 proche de zero ?
+2016-08-24 16:38:59,459 DEBUG: Start: Iteration 632
+2016-08-24 16:38:59,481 DEBUG: View 0 : 0.42654028436
+2016-08-24 16:38:59,491 DEBUG: View 1 : 0.54028436019
+2016-08-24 16:38:59,622 DEBUG: View 2 : 0.601895734597
+2016-08-24 16:38:59,634 DEBUG: View 3 : 0.60663507109
+2016-08-24 16:39:01,506 DEBUG: Best view : Clinic_
+2016-08-24 16:39:52,607 DEBUG: 5.20405936574e-05 proche de zero ?
+2016-08-24 16:39:52,607 DEBUG: Start: Iteration 633
+2016-08-24 16:39:52,629 DEBUG: View 0 : 0.526066350711
+2016-08-24 16:39:52,639 DEBUG: View 1 : 0.559241706161
+2016-08-24 16:39:52,769 DEBUG: View 2 : 0.644549763033
+2016-08-24 16:39:52,780 DEBUG: View 3 : 0.54028436019
+2016-08-24 16:39:54,689 DEBUG: Best view : RANSeq_
+2016-08-24 16:40:46,923 DEBUG: 5.19631340932e-05 proche de zero ?
+2016-08-24 16:40:46,924 DEBUG: Start: Iteration 634
+2016-08-24 16:40:46,945 DEBUG: View 0 : 0.620853080569
+2016-08-24 16:40:46,955 DEBUG: View 1 : 0.682464454976
+2016-08-24 16:40:47,087 DEBUG: View 2 : 0.559241706161
+2016-08-24 16:40:47,098 DEBUG: View 3 : 0.611374407583
+2016-08-24 16:40:49,029 DEBUG: Best view : MiRNA__
+2016-08-24 16:41:40,415 DEBUG: 5.18858065989e-05 proche de zero ?
+2016-08-24 16:41:40,415 DEBUG: Start: Iteration 635
+2016-08-24 16:41:40,439 DEBUG: View 0 : 0.710900473934
+2016-08-24 16:41:40,451 DEBUG: View 1 : 0.511848341232
+2016-08-24 16:41:40,618 DEBUG: View 2 : 0.616113744076
+2016-08-24 16:41:40,632 DEBUG: View 3 : 0.592417061611
+2016-08-24 16:41:42,629 DEBUG: Best view : Methyl_
+2016-08-24 16:42:35,543 DEBUG: 5.1808611268e-05 proche de zero ?
+2016-08-24 16:42:35,543 DEBUG: Start: Iteration 636
+2016-08-24 16:42:35,565 DEBUG: View 0 : 0.488151658768
+2016-08-24 16:42:35,575 DEBUG: View 1 : 0.559241706161
+2016-08-24 16:42:35,711 DEBUG: View 2 : 0.545023696682
+2016-08-24 16:42:35,724 DEBUG: View 3 : 0.687203791469
+2016-08-24 16:42:37,626 DEBUG: Best view : Clinic_
+2016-08-24 16:43:31,235 DEBUG: 5.17315481882e-05 proche de zero ?
+2016-08-24 16:43:31,235 DEBUG: Start: Iteration 637
+2016-08-24 16:43:31,257 DEBUG: View 0 : 0.421800947867
+2016-08-24 16:43:31,267 DEBUG: View 1 : 0.597156398104
+2016-08-24 16:43:31,411 DEBUG: View 2 : 0.601895734597
+2016-08-24 16:43:31,420 DEBUG: View 3 : 0.687203791469
+2016-08-24 16:43:33,273 DEBUG: Best view : Clinic_
+2016-08-24 16:44:24,284 DEBUG: 5.16630764724e-05 proche de zero ?
+2016-08-24 16:44:24,284 DEBUG: Start: Iteration 638
+2016-08-24 16:44:24,306 DEBUG: View 0 : 0.578199052133
+2016-08-24 16:44:24,316 DEBUG: View 1 : 0.620853080569
+2016-08-24 16:44:24,441 DEBUG: View 2 : 0.563981042654
+2016-08-24 16:44:24,450 DEBUG: View 3 : 0.57345971564
+2016-08-24 16:44:26,329 DEBUG: Best view : Methyl_
+2016-08-24 16:45:17,253 DEBUG: 5.15946775578e-05 proche de zero ?
+2016-08-24 16:45:17,253 DEBUG: Start: Iteration 639
+2016-08-24 16:45:17,275 DEBUG: View 0 : 0.379146919431
+2016-08-24 16:45:17,285 DEBUG: View 1 : 0.454976303318
+2016-08-24 16:45:17,408 DEBUG: View 2 : 0.554502369668
+2016-08-24 16:45:17,418 DEBUG: View 3 : 0.502369668246
+2016-08-24 16:45:19,271 DEBUG: Best view : RANSeq_
+2016-08-24 16:46:10,385 DEBUG: 5.15263519555e-05 proche de zero ?
+2016-08-24 16:46:10,386 DEBUG: Start: Iteration 640
+2016-08-24 16:46:10,408 DEBUG: View 0 : 0.582938388626
+2016-08-24 16:46:10,418 DEBUG: View 1 : 0.597156398104
+2016-08-24 16:46:10,548 DEBUG: View 2 : 0.549763033175
+2016-08-24 16:46:10,559 DEBUG: View 3 : 0.559241706161
+2016-08-24 16:46:12,480 DEBUG: Best view : Clinic_
+2016-08-24 16:47:05,838 DEBUG: 5.14581001676e-05 proche de zero ?
+2016-08-24 16:47:05,839 DEBUG: Start: Iteration 641
+2016-08-24 16:47:05,860 DEBUG: View 0 : 0.497630331754
+2016-08-24 16:47:05,870 DEBUG: View 1 : 0.677725118483
+2016-08-24 16:47:05,990 DEBUG: View 2 : 0.578199052133
+2016-08-24 16:47:06,000 DEBUG: View 3 : 0.445497630332
+2016-08-24 16:47:07,908 DEBUG: Best view : MiRNA__
+2016-08-24 16:47:59,781 DEBUG: 5.13899226877e-05 proche de zero ?
+2016-08-24 16:47:59,781 DEBUG: Start: Iteration 642
+2016-08-24 16:47:59,802 DEBUG: View 0 : 0.682464454976
+2016-08-24 16:47:59,812 DEBUG: View 1 : 0.672985781991
+2016-08-24 16:47:59,933 DEBUG: View 2 : 0.554502369668
+2016-08-24 16:47:59,943 DEBUG: View 3 : 0.687203791469
+2016-08-24 16:48:01,831 DEBUG: Best view : Clinic_
+2016-08-24 16:48:54,427 DEBUG: 5.13218200004e-05 proche de zero ?
+2016-08-24 16:48:54,427 DEBUG: Start: Iteration 643
+2016-08-24 16:48:54,450 DEBUG: View 0 : 0.601895734597
+2016-08-24 16:48:54,462 DEBUG: View 1 : 0.630331753555
+2016-08-24 16:48:54,581 DEBUG: View 2 : 0.507109004739
+2016-08-24 16:48:54,590 DEBUG: View 3 : 0.649289099526
+2016-08-24 16:48:56,518 DEBUG: Best view : Clinic_
+2016-08-24 16:49:48,909 DEBUG: 5.12454719495e-05 proche de zero ?
+2016-08-24 16:49:48,909 DEBUG: Start: Iteration 644
+2016-08-24 16:49:48,931 DEBUG: View 0 : 0.492890995261
+2016-08-24 16:49:48,940 DEBUG: View 1 : 0.60663507109
+2016-08-24 16:49:49,056 DEBUG: View 2 : 0.483412322275
+2016-08-24 16:49:49,065 DEBUG: View 3 : 0.60663507109
+2016-08-24 16:49:50,963 DEBUG: Best view : Clinic_
+2016-08-24 16:50:43,820 DEBUG: 5.11692577604e-05 proche de zero ?
+2016-08-24 16:50:43,820 DEBUG: Start: Iteration 645
+2016-08-24 16:50:43,842 DEBUG: View 0 : 0.521327014218
+2016-08-24 16:50:43,852 DEBUG: View 1 : 0.725118483412
+2016-08-24 16:50:43,974 DEBUG: View 2 : 0.545023696682
+2016-08-24 16:50:43,983 DEBUG: View 3 : 0.625592417062
+2016-08-24 16:50:45,972 DEBUG: Best view : MiRNA__
+2016-08-24 16:51:38,015 DEBUG: 5.10931774675e-05 proche de zero ?
+2016-08-24 16:51:38,015 DEBUG: Start: Iteration 646
+2016-08-24 16:51:38,036 DEBUG: View 0 : 0.431279620853
+2016-08-24 16:51:38,046 DEBUG: View 1 : 0.777251184834
+2016-08-24 16:51:38,158 DEBUG: View 2 : 0.60663507109
+2016-08-24 16:51:38,167 DEBUG: View 3 : 0.668246445498
+2016-08-24 16:51:40,048 DEBUG: Best view : MiRNA__
+2016-08-24 16:52:32,446 DEBUG: 5.10172311008e-05 proche de zero ?
+2016-08-24 16:52:32,447 DEBUG: Start: Iteration 647
+2016-08-24 16:52:32,468 DEBUG: View 0 : 0.706161137441
+2016-08-24 16:52:32,478 DEBUG: View 1 : 0.654028436019
+2016-08-24 16:52:32,592 DEBUG: View 2 : 0.592417061611
+2016-08-24 16:52:32,601 DEBUG: View 3 : 0.54028436019
+2016-08-24 16:52:34,507 DEBUG: Best view : Methyl_
+2016-08-24 16:53:27,202 DEBUG: 5.09414186855e-05 proche de zero ?
+2016-08-24 16:53:27,202 DEBUG: Start: Iteration 648
+2016-08-24 16:53:27,223 DEBUG: View 0 : 0.635071090047
+2016-08-24 16:53:27,233 DEBUG: View 1 : 0.654028436019
+2016-08-24 16:53:27,354 DEBUG: View 2 : 0.507109004739
+2016-08-24 16:53:27,364 DEBUG: View 3 : 0.497630331754
+2016-08-24 16:53:29,269 DEBUG: Best view : MiRNA__
+2016-08-24 16:54:21,571 DEBUG: 5.08657402423e-05 proche de zero ?
+2016-08-24 16:54:21,571 DEBUG: Start: Iteration 649
+2016-08-24 16:54:21,593 DEBUG: View 0 : 0.715639810427
+2016-08-24 16:54:21,605 DEBUG: View 1 : 0.630331753555
+2016-08-24 16:54:21,732 DEBUG: View 2 : 0.559241706161
+2016-08-24 16:54:21,741 DEBUG: View 3 : 0.54028436019
+2016-08-24 16:54:23,723 DEBUG: Best view : Methyl_
+2016-08-24 16:55:16,895 DEBUG: 5.07901957873e-05 proche de zero ?
+2016-08-24 16:55:16,895 DEBUG: Start: Iteration 650
+2016-08-24 16:55:16,916 DEBUG: View 0 : 0.483412322275
+2016-08-24 16:55:16,927 DEBUG: View 1 : 0.549763033175
+2016-08-24 16:55:17,048 DEBUG: View 2 : 0.587677725118
+2016-08-24 16:55:17,057 DEBUG: View 3 : 0.578199052133
+2016-08-24 16:55:19,081 DEBUG: Best view : RANSeq_
+2016-08-24 16:56:11,954 DEBUG: 5.07147853324e-05 proche de zero ?
+2016-08-24 16:56:11,954 DEBUG: Start: Iteration 651
+2016-08-24 16:56:11,976 DEBUG: View 0 : 0.568720379147
+2016-08-24 16:56:11,986 DEBUG: View 1 : 0.464454976303
+2016-08-24 16:56:12,106 DEBUG: View 2 : 0.582938388626
+2016-08-24 16:56:12,115 DEBUG: View 3 : 0.611374407583
+2016-08-24 16:56:14,038 DEBUG: Best view : Clinic_
+2016-08-24 16:57:06,332 DEBUG: 5.0639508885e-05 proche de zero ?
+2016-08-24 16:57:06,332 DEBUG: Start: Iteration 652
+2016-08-24 16:57:06,355 DEBUG: View 0 : 0.521327014218
+2016-08-24 16:57:06,365 DEBUG: View 1 : 0.445497630332
+2016-08-24 16:57:06,476 DEBUG: View 2 : 0.578199052133
+2016-08-24 16:57:06,485 DEBUG: View 3 : 0.630331753555
+2016-08-24 16:57:08,488 DEBUG: Best view : Clinic_
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-134900-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-134900-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..2eee6f4a93cc7cb0798b9e25df10e6af0e680add
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-134900-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,19 @@
+2016-08-24 13:49:00,493 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 13:49:00,493 INFO: Info: Labels used: No, Yes
+2016-08-24 13:49:00,494 INFO: Info: Length of dataset:347
+2016-08-24 13:49:00,507 INFO: ### Main Programm for Multiview Classification
+2016-08-24 13:49:00,507 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Fusion ; Cores : 4
+2016-08-24 13:49:00,508 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 13:49:00,508 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 13:49:00,509 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 13:49:00,509 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 13:49:00,509 INFO: Done: Read Database Files
+2016-08-24 13:49:00,509 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 13:49:00,513 INFO: Done: Determine validation split
+2016-08-24 13:49:00,513 INFO: Start: Determine 5 folds
+2016-08-24 13:49:00,522 INFO: Info: Length of Learning Sets: 196
+2016-08-24 13:49:00,522 INFO: Info: Length of Testing Sets: 48
+2016-08-24 13:49:00,522 INFO: Info: Length of Validation Set: 103
+2016-08-24 13:49:00,522 INFO: Done: Determine folds
+2016-08-24 13:49:00,522 INFO: Start: Learning with Fusion and 5 folds
+2016-08-24 13:49:00,522 INFO: Start: Fold number 1
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-135019-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-135019-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..b60809d54d95b042f5111084b02092729cdf943a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-135019-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,19 @@
+2016-08-24 13:50:19,043 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 13:50:19,043 INFO: Info: Labels used: No, Yes
+2016-08-24 13:50:19,044 INFO: Info: Length of dataset:347
+2016-08-24 13:50:19,045 INFO: ### Main Programm for Multiview Classification
+2016-08-24 13:50:19,045 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Fusion ; Cores : 4
+2016-08-24 13:50:19,046 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 13:50:19,046 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 13:50:19,047 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 13:50:19,047 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 13:50:19,047 INFO: Done: Read Database Files
+2016-08-24 13:50:19,047 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 13:50:19,051 INFO: Done: Determine validation split
+2016-08-24 13:50:19,051 INFO: Start: Determine 5 folds
+2016-08-24 13:50:19,059 INFO: Info: Length of Learning Sets: 196
+2016-08-24 13:50:19,059 INFO: Info: Length of Testing Sets: 48
+2016-08-24 13:50:19,059 INFO: Info: Length of Validation Set: 103
+2016-08-24 13:50:19,059 INFO: Done: Determine folds
+2016-08-24 13:50:19,059 INFO: Start: Learning with Fusion and 5 folds
+2016-08-24 13:50:19,059 INFO: Start: Fold number 1
diff --git a/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-135102-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-135102-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..0e0edeb3c203310af4c7d9ab5524fa25fb8fc957
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Multiview/Results/20160824-135102-CMultiV-Fusion-Methyl_MiRNA_RNASEQ_Clinical-ModifiedMultiOmic-LOG.log
@@ -0,0 +1,19 @@
+2016-08-24 13:51:02,963 INFO: Start: Read HDF5 Database Files for ModifiedMultiOmic
+2016-08-24 13:51:02,964 INFO: Info: Labels used: No, Yes
+2016-08-24 13:51:02,964 INFO: Info: Length of dataset:347
+2016-08-24 13:51:02,965 INFO: ### Main Programm for Multiview Classification
+2016-08-24 13:51:02,966 INFO: ### Classification - Database : ModifiedMultiOmic ; Views : Methyl, MiRNA, RNASEQ, Clinical ; Algorithm : Fusion ; Cores : 4
+2016-08-24 13:51:02,966 INFO: Info: Shape of Methyl_ :(347, 25978)
+2016-08-24 13:51:02,966 INFO: Info: Shape of MiRNA__ :(347, 1046)
+2016-08-24 13:51:02,967 INFO: Info: Shape of RANSeq_ :(347, 73599)
+2016-08-24 13:51:02,967 INFO: Info: Shape of Clinic_ :(347, 127)
+2016-08-24 13:51:02,967 INFO: Done: Read Database Files
+2016-08-24 13:51:02,968 INFO: Start: Determine validation split for ratio 0.7
+2016-08-24 13:51:02,971 INFO: Done: Determine validation split
+2016-08-24 13:51:02,971 INFO: Start: Determine 5 folds
+2016-08-24 13:51:02,981 INFO: Info: Length of Learning Sets: 196
+2016-08-24 13:51:02,981 INFO: Info: Length of Testing Sets: 48
+2016-08-24 13:51:02,981 INFO: Info: Length of Validation Set: 103
+2016-08-24 13:51:02,981 INFO: Done: Determine folds
+2016-08-24 13:51:02,981 INFO: Start: Learning with Fusion and 5 folds
+2016-08-24 13:51:02,982 INFO: Start: Fold number 1
diff --git a/Code/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG
similarity index 100%
rename from Code/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG
diff --git a/Code/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_04_26-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log
diff --git a/Code/Multiview/Results/2016_04_26-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_04_26-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_04_26-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_04_26-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log
diff --git a/Code/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG
similarity index 100%
rename from Code/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG
diff --git a/Code/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Fusion-phog-hist_decaf_cq-hist-Awa-LOG.log
diff --git a/Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_decaf-Awa-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_decaf-Awa-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_decaf-Awa-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_decaf-Awa-LOG.log
diff --git a/Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG
similarity index 100%
rename from Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG
diff --git a/Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log
diff --git a/Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG
similarity index 100%
rename from Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG
diff --git a/Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_16-CMultiV-Mumbo-phog-hist_decaf_cq-hist-Awa-LOG.log
diff --git a/Code/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG
similarity index 100%
rename from Code/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG
diff --git a/Code/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_20-CMultiV-Mumbo-phog-hist_cq-hist_surf-hist-Awa-LOG.log
diff --git a/Code/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG
similarity index 100%
rename from Code/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG
diff --git a/Code/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG.log
similarity index 100%
rename from Code/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG.log
rename to Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_23-CMultiV-Mumbo-Methylation_RNA-seq_miRNA-MultiOmic-LOG.log
diff --git a/Code/Multiview/Results/2016_06_23-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG b/Code/MonoMutliViewClassifiers/Multiview/Results/2016_06_23-CMultiV-Mumbo-RGB_HOG_SIFT-MultiOmic-LOG
similarity index 100%
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diff --git a/Code/Multiview/run.py b/Code/MonoMutliViewClassifiers/Multiview/run.py
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index 3c60436dbb6dcad9e53111d2fb6af820873f767f..7a3b56c14df4a47148331c8aa740f6417d2f9d9d 100644
--- a/Code/Multiview/run.py
+++ b/Code/MonoMutliViewClassifiers/Multiview/run.py
@@ -1,6 +1,6 @@
# coding=utf-8
import os
-os.system('python ExecMultiview.py -log --name ModifiedMultiOmic --type .csv --views Methyl:MiRNA:RNASEQ:Clinical --pathF /home/bbauvin/Documents/Data/Data_multi_omics/ --CL_split 0.7 --CL_nbFolds 2 --CL_nb_class 2 --CL_classes Positive:Negative --CL_type Fusion --CL_cores 4 --FU_type EarlyFusion --FU_method WeightedLinear')
+os.system('python ExecMultiview.py -log --name ModifiedMultiOmic --type .hdf5 --views Methyl:MiRNA:RNASEQ:Clinical --pathF /home/bbauvin/Documents/Data/Data_multi_omics/ --CL_split 0.7 --CL_nbFolds 5 --CL_nb_class 2 --CL_classes Positive:Negative --CL_type Fusion --CL_cores 4 --FU_type EarlyFusion --FU_method WeightedLinear')
# /donnees/pj_bdd_bbauvin/Data_multi_omics/
#
# /home/bbauvin/Documents/Data/Data_multi_omics/
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diff --git a/Code/Results/20160822-142903-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-142903-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-142943-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-142943-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-143254-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-143254-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-143512-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-143512-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-143553-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-143553-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-150532-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-150532-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-150705-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-150705-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-150714-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-150714-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-152212-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-152212-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-153503-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-153503-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-154718-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-154718-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-155011-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-155011-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-155240-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-155240-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160822-155839-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160822-155839-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160823-105758-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-105758-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160823-110509-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-110509-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160823-110659-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-110659-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160823-110859-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-110859-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160823-111036-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-111036-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/Results/20160823-111124-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-111124-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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diff --git a/Code/MonoMutliViewClassifiers/Results/20160823-111945-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-111945-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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index 0000000000000000000000000000000000000000..fd3749c7189ef9c1be055f1c47708747136ec41e
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+++ b/Code/MonoMutliViewClassifiers/Results/20160823-111945-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,32 @@
+2016-08-23 11:19:45,964 INFO: Begginging
+2016-08-23 11:19:45,968 INFO: ### Main Programm for Multiview Classification
+2016-08-23 11:19:45,968 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-23 11:19:45,968 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-23 11:19:45,969 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-23 11:19:45,969 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-23 11:19:45,970 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-23 11:19:45,970 INFO: Done: Read Database Files
+2016-08-23 11:19:45,970 INFO: Start: Determine validation split for ratio 0.9
+2016-08-23 11:19:45,973 INFO: Done: Determine validation split
+2016-08-23 11:19:45,973 INFO: Start: Determine 2 folds
+2016-08-23 11:19:45,998 INFO: Info: Length of Learning Sets: 157
+2016-08-23 11:19:45,999 INFO: Info: Length of Testing Sets: 156
+2016-08-23 11:19:45,999 INFO: Info: Length of Validation Set: 34
+2016-08-23 11:19:45,999 INFO: Done: Determine folds
+2016-08-23 11:19:45,999 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-23 11:19:45,999 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-23 11:20:15,162 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-23 11:20:15,162 INFO: Start: Fold number 1
+2016-08-23 11:20:15,177 DEBUG: Start: Iteration 1
+2016-08-23 11:20:15,221 DEBUG: View 0 : 0.715083798883
+2016-08-23 11:20:15,235 DEBUG: View 1 : 0.720670391061
+2016-08-23 11:20:15,275 DEBUG: View 2 : 0.385474860335
+2016-08-23 11:20:15,285 DEBUG: View 3 : 0.54748603352
+2016-08-23 11:20:15,325 DEBUG: Best view : RANSeq
+2016-08-23 11:20:15,334 DEBUG: Start: Iteration 2
+2016-08-23 11:20:15,355 DEBUG: View 0 : 0.357541899441
+2016-08-23 11:20:15,364 DEBUG: View 1 : 0.290502793296
+2016-08-23 11:20:15,405 DEBUG: View 2 : 0.614525139665
+2016-08-23 11:20:15,414 DEBUG: View 3 : 0.357541899441
+2016-08-23 11:20:15,460 DEBUG: Best view : RANSeq
+2016-08-23 11:20:15,470 INFO: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160823-112110-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160823-112110-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
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+++ b/Code/MonoMutliViewClassifiers/Results/20160823-112110-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,157 @@
+2016-08-23 11:21:10,029 INFO: Begginging
+2016-08-23 11:21:10,033 INFO: ### Main Programm for Multiview Classification
+2016-08-23 11:21:10,033 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-23 11:21:10,034 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-23 11:21:10,034 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-23 11:21:10,034 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-23 11:21:10,035 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-23 11:21:10,035 INFO: Done: Read Database Files
+2016-08-23 11:21:10,035 INFO: Start: Determine validation split for ratio 0.9
+2016-08-23 11:21:10,038 INFO: Done: Determine validation split
+2016-08-23 11:21:10,038 INFO: Start: Determine 2 folds
+2016-08-23 11:21:10,056 INFO: Info: Length of Learning Sets: 157
+2016-08-23 11:21:10,056 INFO: Info: Length of Testing Sets: 156
+2016-08-23 11:21:10,056 INFO: Info: Length of Validation Set: 34
+2016-08-23 11:21:10,056 INFO: Done: Determine folds
+2016-08-23 11:21:10,056 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-23 11:21:10,056 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-23 11:21:38,101 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-23 11:21:38,101 INFO: Start: Fold number 1
+2016-08-23 11:21:38,116 DEBUG: Start: Iteration 1
+2016-08-23 11:21:38,135 DEBUG: View 0 : 0.619047619048
+2016-08-23 11:21:38,144 DEBUG: View 1 : 0.696428571429
+2016-08-23 11:21:38,178 DEBUG: View 2 : 0.303571428571
+2016-08-23 11:21:38,187 DEBUG: View 3 : 0.696428571429
+2016-08-23 11:21:38,223 DEBUG: Best view : MiRNA_
+2016-08-23 11:21:38,231 DEBUG: Start: Iteration 2
+2016-08-23 11:21:38,249 DEBUG: View 0 : 0.315476190476
+2016-08-23 11:21:38,258 DEBUG: View 1 : 0.690476190476
+2016-08-23 11:21:38,302 DEBUG: View 2 : 0.589285714286
+2016-08-23 11:21:38,312 DEBUG: View 3 : 0.660714285714
+2016-08-23 11:21:38,353 DEBUG: Best view : MiRNA_
+2016-08-23 11:21:38,361 INFO: Start: Classification
+2016-08-23 11:21:38,625 INFO: Done: Fold number 1
+2016-08-23 11:21:38,626 INFO: Start: Fold number 2
+2016-08-23 11:21:38,640 DEBUG: Start: Iteration 1
+2016-08-23 11:21:38,657 DEBUG: View 0 : 0.710227272727
+2016-08-23 11:21:38,666 DEBUG: View 1 : 0.477272727273
+2016-08-23 11:21:38,704 DEBUG: View 2 : 0.289772727273
+2016-08-23 11:21:38,714 DEBUG: View 3 : 0.289772727273
+2016-08-23 11:21:38,751 DEBUG: Best view : Methyl
+2016-08-23 11:21:38,759 DEBUG: Start: Iteration 2
+2016-08-23 11:21:38,777 DEBUG: View 0 : 0.710227272727
+2016-08-23 11:21:38,787 DEBUG: View 1 : 0.625
+2016-08-23 11:21:38,832 DEBUG: View 2 : 0.392045454545
+2016-08-23 11:21:38,842 DEBUG: View 3 : 0.306818181818
+2016-08-23 11:21:38,885 DEBUG: Best view : Methyl
+2016-08-23 11:21:38,894 INFO: Start: Classification
+2016-08-23 11:21:39,183 INFO: Done: Fold number 2
+2016-08-23 11:21:39,183 INFO: Done: Classification
+2016-08-23 11:21:39,183 INFO: Info: Time for Classification: 29[s]
+2016-08-23 11:21:39,183 INFO: Start: Result Analysis for Mumbo
+2016-08-23 11:21:39,918 INFO: Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 70.3327922078
+ -On Test : 73.0769230769
+ -On Validation : 73.5294117647
+
+Dataset info :
+ -Database name : MultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA_, RNASeq, Clinic
+ -2 folds
+ - Validation set length : 34 for learning rate : 0.9
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 2
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA_
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASeq
+ -DecisionTree with depth 1.0, sub-sampled at 0.0065 on Clinic
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl :
+ - Mean average Accuracy : 0.467261904762
+ - Percentage of time chosen : 0.0
+ - On MiRNA_ :
+ - Mean average Accuracy : 0.693452380952
+ - Percentage of time chosen : 1.0
+ - On RANSeq :
+ - Mean average Accuracy : 0.446428571429
+ - Percentage of time chosen : 0.0
+ - On Clinic :
+ - Mean average Accuracy : 0.678571428571
+ - Percentage of time chosen : 0.0
+ - Fold 1
+ - On Methyl :
+ - Mean average Accuracy : 0.710227272727
+ - Percentage of time chosen : 1.0
+ - On MiRNA_ :
+ - Mean average Accuracy : 0.551136363636
+ - Percentage of time chosen : 0.0
+ - On RANSeq :
+ - Mean average Accuracy : 0.340909090909
+ - Percentage of time chosen : 0.0
+ - On Clinic :
+ - Mean average Accuracy : 0.298295454545
+ - Percentage of time chosen : 0.0
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 69.6428571429
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : MiRNA_
+ Fold 2
+ Accuracy on train : 71.0227272727
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : Methyl
+ - Mean :
+ Accuracy on train : 70.3327922078
+ Accuracy on test : 73.0769230769
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 69.6428571429
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : MiRNA_
+ Fold 2
+ Accuracy on train : 71.0227272727
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : Methyl
+ - Mean :
+ Accuracy on train : 70.3327922078
+ Accuracy on test : 73.0769230769
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:00:28 0:00:00
+ Fold 2 0:00:28 0:00:00
+ Total 0:00:57 0:00:00
+ So a total classification time of 0:00:29.
+
+
+2016-08-23 11:21:40,125 INFO: Done: Result Analysis
+2016-08-23 11:21:40,126 INFO: ### Main Programm for Multiview Classification
+2016-08-23 11:21:40,126 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-23 11:21:40,127 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-23 11:21:40,127 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-23 11:21:40,127 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-23 11:21:40,128 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-23 11:21:40,128 INFO: Done: Read Database Files
+2016-08-23 11:21:40,128 INFO: Start: Determine validation split for ratio 0.9
+2016-08-23 11:21:40,131 INFO: Done: Determine validation split
+2016-08-23 11:21:40,131 INFO: Start: Determine 2 folds
+2016-08-23 11:21:40,145 INFO: Info: Length of Learning Sets: 157
+2016-08-23 11:21:40,145 INFO: Info: Length of Testing Sets: 156
+2016-08-23 11:21:40,145 INFO: Info: Length of Validation Set: 34
+2016-08-23 11:21:40,145 INFO: Done: Determine folds
+2016-08-23 11:21:40,145 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-23 11:21:40,145 INFO: Start: Gridsearching best settings for monoview classifiers
diff --git a/Code/MonoMutliViewClassifiers/Results/20160823-112139Results-Mumbo-Methyl-MiRNA_-RNASeq-Clinic-Yes-No-learnRate0.9-MultiOmic-accuracyByIteration.png b/Code/MonoMutliViewClassifiers/Results/20160823-112139Results-Mumbo-Methyl-MiRNA_-RNASeq-Clinic-Yes-No-learnRate0.9-MultiOmic-accuracyByIteration.png
new file mode 100644
index 0000000000000000000000000000000000000000..532f595c4dfe64597162c05541121c52a3751a4c
Binary files /dev/null and b/Code/MonoMutliViewClassifiers/Results/20160823-112139Results-Mumbo-Methyl-MiRNA_-RNASeq-Clinic-Yes-No-learnRate0.9-MultiOmic-accuracyByIteration.png differ
diff --git a/Code/MonoMutliViewClassifiers/Results/20160823-112139Results-Mumbo-Methyl-MiRNA_-RNASeq-Clinic-Yes-No-learnRate0.9-MultiOmic.txt b/Code/MonoMutliViewClassifiers/Results/20160823-112139Results-Mumbo-Methyl-MiRNA_-RNASeq-Clinic-Yes-No-learnRate0.9-MultiOmic.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ad390878712c48eebe2f1c3ed5736226ff502dfd
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160823-112139Results-Mumbo-Methyl-MiRNA_-RNASeq-Clinic-Yes-No-learnRate0.9-MultiOmic.txt
@@ -0,0 +1,88 @@
+ Result for Multiview classification with Mumbo
+
+Average accuracy :
+ -On Train : 70.3327922078
+ -On Test : 73.0769230769
+ -On Validation : 73.5294117647
+
+Dataset info :
+ -Database name : MultiOmic
+ -Labels : No, Yes
+ -Views : Methyl, MiRNA_, RNASeq, Clinic
+ -2 folds
+ - Validation set length : 34 for learning rate : 0.9
+
+Classification configuration :
+ -Algorithm used : Mumbo
+ -Iterations : 2
+ -Weak Classifiers : DecisionTree with depth 1.0, sub-sampled at 0.006 on Methyl
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on MiRNA_
+ -DecisionTree with depth 1.0, sub-sampled at 0.006 on RNASeq
+ -DecisionTree with depth 1.0, sub-sampled at 0.0065 on Clinic
+
+ Mean average accuracies and stats for each fold :
+ - Fold 0
+ - On Methyl :
+ - Mean average Accuracy : 0.467261904762
+ - Percentage of time chosen : 0.0
+ - On MiRNA_ :
+ - Mean average Accuracy : 0.693452380952
+ - Percentage of time chosen : 1.0
+ - On RANSeq :
+ - Mean average Accuracy : 0.446428571429
+ - Percentage of time chosen : 0.0
+ - On Clinic :
+ - Mean average Accuracy : 0.678571428571
+ - Percentage of time chosen : 0.0
+ - Fold 1
+ - On Methyl :
+ - Mean average Accuracy : 0.710227272727
+ - Percentage of time chosen : 1.0
+ - On MiRNA_ :
+ - Mean average Accuracy : 0.551136363636
+ - Percentage of time chosen : 0.0
+ - On RANSeq :
+ - Mean average Accuracy : 0.340909090909
+ - Percentage of time chosen : 0.0
+ - On Clinic :
+ - Mean average Accuracy : 0.298295454545
+ - Percentage of time chosen : 0.0
+
+ For each iteration :
+ - Iteration 1
+ Fold 1
+ Accuracy on train : 69.6428571429
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : MiRNA_
+ Fold 2
+ Accuracy on train : 71.0227272727
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : Methyl
+ - Mean :
+ Accuracy on train : 70.3327922078
+ Accuracy on test : 73.0769230769
+ - Iteration 2
+ Fold 1
+ Accuracy on train : 69.6428571429
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : MiRNA_
+ Fold 2
+ Accuracy on train : 71.0227272727
+ Accuracy on test : 73.0769230769
+ Accuracy on validation : 73.5294117647
+ Selected View : Methyl
+ - Mean :
+ Accuracy on train : 70.3327922078
+ Accuracy on test : 73.0769230769
+
+Computation time on 1 cores :
+ Database extraction time : 0:00:00
+ Learn Prediction
+ Fold 1 0:00:28 0:00:00
+ Fold 2 0:00:28 0:00:00
+ Total 0:00:57 0:00:00
+ So a total classification time of 0:00:29.
+
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-150940-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-150940-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..78212b4eff0eabc3fa3fa8aa7ffc302cede0ee2f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-150940-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,18 @@
+2016-08-24 15:09:40,867 INFO: Begginging
+2016-08-24 15:09:40,868 INFO: ### Main Programm for Multiview Classification
+2016-08-24 15:09:40,869 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 15:09:40,869 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-24 15:09:40,869 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-24 15:09:40,870 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-24 15:09:40,870 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-24 15:09:40,870 INFO: Done: Read Database Files
+2016-08-24 15:09:40,870 INFO: Start: Determine validation split for ratio 0.9
+2016-08-24 15:09:40,873 INFO: Done: Determine validation split
+2016-08-24 15:09:40,873 INFO: Start: Determine 2 folds
+2016-08-24 15:09:40,885 INFO: Info: Length of Learning Sets: 157
+2016-08-24 15:09:40,885 INFO: Info: Length of Testing Sets: 156
+2016-08-24 15:09:40,886 INFO: Info: Length of Validation Set: 34
+2016-08-24 15:09:40,886 INFO: Done: Determine folds
+2016-08-24 15:09:40,886 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 15:09:40,886 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 15:09:40,886 DEBUG: Start: Gridsearch for DecisionTree on Methyl
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-151006-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-151006-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..12fc0bf7d4fbf27971166dc3e3eae44e0b555d5b
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-151006-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,24 @@
+2016-08-24 15:10:06,969 INFO: Begginging
+2016-08-24 15:10:06,971 INFO: ### Main Programm for Multiview Classification
+2016-08-24 15:10:06,971 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 15:10:06,971 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-24 15:10:06,972 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-24 15:10:06,972 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-24 15:10:06,973 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-24 15:10:06,973 INFO: Done: Read Database Files
+2016-08-24 15:10:06,973 INFO: Start: Determine validation split for ratio 0.9
+2016-08-24 15:10:06,975 INFO: Done: Determine validation split
+2016-08-24 15:10:06,976 INFO: Start: Determine 2 folds
+2016-08-24 15:10:06,990 INFO: Info: Length of Learning Sets: 157
+2016-08-24 15:10:06,990 INFO: Info: Length of Testing Sets: 156
+2016-08-24 15:10:06,990 INFO: Info: Length of Validation Set: 34
+2016-08-24 15:10:06,990 INFO: Done: Determine folds
+2016-08-24 15:10:06,990 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 15:10:06,990 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 15:10:06,991 DEBUG: Start: Gridsearch for DecisionTree on Methyl
+2016-08-24 15:10:14,842 DEBUG: Info: Best Reslut : 0.555043227666
+2016-08-24 15:10:14,843 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 15:10:14,843 DEBUG: Start: Gridsearch for DecisionTree on MiRNA_
+2016-08-24 15:10:17,017 DEBUG: Info: Best Reslut : 0.524956772334
+2016-08-24 15:10:17,017 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 15:10:17,018 DEBUG: Start: Gridsearch for DecisionTree on RANSeq
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-151503-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-151503-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..6611dd3aa69f01dce00f27f4f49d0e0fe7c7c99a
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-151503-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 15:15:03,256 INFO: Begginging
+2016-08-24 15:15:03,268 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:15:03,268 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:15:03,268 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:15:03,300 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:15:03,300 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:15:03,300 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:15:03,300 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-151604-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-151604-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..d08108a0ee9942b041d3b43f11b829e07301a08e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-151604-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 15:16:04,064 INFO: Begginging
+2016-08-24 15:16:04,080 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:16:04,080 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:16:04,080 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:16:04,136 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:16:04,136 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:16:04,136 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:16:04,136 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-151656-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-151656-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..f5754b56cd33c1fe66168606d1a6ee9d5024ec3e
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-151656-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 15:16:56,323 INFO: Begginging
+2016-08-24 15:16:56,345 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:16:56,345 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:16:56,345 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:16:56,394 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:16:56,395 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:16:56,395 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:16:56,395 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-151836-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-151836-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..e05049d157c4d90566ab8ce49b45efffa1ea12da
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-151836-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,74 @@
+2016-08-24 15:18:36,539 INFO: Begginging
+2016-08-24 15:18:36,572 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:18:36,573 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:18:36,573 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:18:36,682 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:18:36,682 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:18:36,682 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:18:36,682 DEBUG: Start: Classification
+2016-08-24 15:18:43,218 DEBUG: Info: Time for Classification: 6.44028186798[s]
+2016-08-24 15:18:43,218 DEBUG: Done: Classification
+2016-08-24 15:18:43,248 DEBUG: Start: Statistic Results
+2016-08-24 15:18:43,249 DEBUG: Info: Classification report:
+2016-08-24 15:18:43,255 DEBUG:
+ precision recall f1-score support
+
+ Non 0.91 0.87 0.89 23
+ Oui 0.77 0.83 0.80 12
+
+avg / total 0.86 0.86 0.86 35
+
+2016-08-24 15:18:43,277 DEBUG: Info: Statistics:
+2016-08-24 15:18:43,304 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.857142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.844444
+5 Mean of F1-Score of top 20 classes by F1-Score 0.844444
+6 Mean of F1-Score of top 30 classes by F1-Score 0.844444
+2016-08-24 15:18:43,305 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:18:47,165 DEBUG: Done: Statistic Results
+2016-08-24 15:18:47,165 DEBUG: Start: Plot Result
+2016-08-24 15:18:47,389 DEBUG: Done: Plot Result
+2016-08-24 15:18:47,567 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:18:47,567 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 15:18:47,567 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:18:47,603 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:18:47,604 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:18:47,604 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:18:47,604 DEBUG: Start: Classification
+2016-08-24 15:18:57,893 DEBUG: Info: Time for Classification: 10.3103861809[s]
+2016-08-24 15:18:57,893 DEBUG: Done: Classification
+2016-08-24 15:18:58,420 DEBUG: Start: Statistic Results
+2016-08-24 15:18:58,421 DEBUG: Info: Classification report:
+2016-08-24 15:18:58,422 DEBUG:
+ precision recall f1-score support
+
+ Non 0.88 0.92 0.90 24
+ Oui 0.80 0.73 0.76 11
+
+avg / total 0.85 0.86 0.86 35
+
+2016-08-24 15:18:58,432 DEBUG: Info: Statistics:
+2016-08-24 15:18:58,440 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.857142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.829932
+5 Mean of F1-Score of top 20 classes by F1-Score 0.829932
+6 Mean of F1-Score of top 30 classes by F1-Score 0.829932
+2016-08-24 15:18:58,440 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:18:58,814 DEBUG: Done: Statistic Results
+2016-08-24 15:18:58,814 DEBUG: Start: Plot Result
+2016-08-24 15:18:59,544 DEBUG: Done: Plot Result
+2016-08-24 15:18:59,780 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:18:59,780 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 15:18:59,780 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:18:59,793 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:18:59,793 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:18:59,793 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:18:59,793 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-152149-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-152149-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..113ec1faddf001e6ee7d7834149ced64de7d4e71
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-152149-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,74 @@
+2016-08-24 15:21:49,852 INFO: Begginging
+2016-08-24 15:21:49,900 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:21:49,900 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:21:49,900 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:21:49,944 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:21:49,944 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:21:49,944 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:21:49,944 DEBUG: Start: Classification
+2016-08-24 15:21:56,634 DEBUG: Info: Time for Classification: 6.73074197769[s]
+2016-08-24 15:21:56,634 DEBUG: Done: Classification
+2016-08-24 15:21:56,641 DEBUG: Start: Statistic Results
+2016-08-24 15:21:56,642 DEBUG: Info: Classification report:
+2016-08-24 15:21:56,643 DEBUG:
+ precision recall f1-score support
+
+ Non 1.00 0.78 0.88 27
+ Oui 0.57 1.00 0.73 8
+
+avg / total 0.90 0.83 0.84 35
+
+2016-08-24 15:21:56,645 DEBUG: Info: Statistics:
+2016-08-24 15:21:56,659 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.828571428571
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.801136
+5 Mean of F1-Score of top 20 classes by F1-Score 0.801136
+6 Mean of F1-Score of top 30 classes by F1-Score 0.801136
+2016-08-24 15:21:56,659 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:21:58,311 DEBUG: Done: Statistic Results
+2016-08-24 15:21:58,311 DEBUG: Start: Plot Result
+2016-08-24 15:21:58,529 DEBUG: Done: Plot Result
+2016-08-24 15:21:58,545 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:21:58,546 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 15:21:58,546 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:21:58,567 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:21:58,567 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:21:58,567 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:21:58,567 DEBUG: Start: Classification
+2016-08-24 15:22:09,219 DEBUG: Info: Time for Classification: 10.6697540283[s]
+2016-08-24 15:22:09,219 DEBUG: Done: Classification
+2016-08-24 15:22:09,835 DEBUG: Start: Statistic Results
+2016-08-24 15:22:09,836 DEBUG: Info: Classification report:
+2016-08-24 15:22:09,837 DEBUG:
+ precision recall f1-score support
+
+ Non 0.88 0.84 0.86 25
+ Oui 0.64 0.70 0.67 10
+
+avg / total 0.81 0.80 0.80 35
+
+2016-08-24 15:22:09,839 DEBUG: Info: Statistics:
+2016-08-24 15:22:09,847 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.761905
+5 Mean of F1-Score of top 20 classes by F1-Score 0.761905
+6 Mean of F1-Score of top 30 classes by F1-Score 0.761905
+2016-08-24 15:22:09,847 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:22:10,192 DEBUG: Done: Statistic Results
+2016-08-24 15:22:10,193 DEBUG: Start: Plot Result
+2016-08-24 15:22:11,137 DEBUG: Done: Plot Result
+2016-08-24 15:22:11,149 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:22:11,149 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 15:22:11,149 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:22:11,164 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:22:11,164 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:22:11,164 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:22:11,164 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-153240-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-153240-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..75472f2a548bf898da017ae173d51de0df658faa
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-153240-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,107 @@
+2016-08-24 15:32:40,924 INFO: Begginging
+2016-08-24 15:32:40,949 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:32:40,950 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:32:40,950 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:32:41,016 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:32:41,016 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:32:41,016 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:32:41,016 DEBUG: Start: Classification
+2016-08-24 15:32:51,899 DEBUG: Info: Time for Classification: 10.9459741116[s]
+2016-08-24 15:32:51,899 DEBUG: Done: Classification
+2016-08-24 15:32:51,901 DEBUG: Start: Statistic Results
+2016-08-24 15:32:51,902 DEBUG: Info: Classification report:
+2016-08-24 15:32:51,903 DEBUG:
+ precision recall f1-score support
+
+ Non 0.95 0.87 0.91 23
+ Oui 0.79 0.92 0.85 12
+
+avg / total 0.90 0.89 0.89 35
+
+2016-08-24 15:32:51,916 DEBUG: Info: Statistics:
+2016-08-24 15:32:51,924 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.885714285714
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.877622
+5 Mean of F1-Score of top 20 classes by F1-Score 0.877622
+6 Mean of F1-Score of top 30 classes by F1-Score 0.877622
+2016-08-24 15:32:51,924 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:32:53,052 DEBUG: Done: Statistic Results
+2016-08-24 15:32:53,052 DEBUG: Start: Plot Result
+2016-08-24 15:32:53,269 DEBUG: Done: Plot Result
+2016-08-24 15:32:53,283 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:32:53,283 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 15:32:53,283 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:32:53,298 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:32:53,298 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:32:53,298 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:32:53,298 DEBUG: Start: Classification
+2016-08-24 15:33:03,233 DEBUG: Info: Time for Classification: 9.94683003426[s]
+2016-08-24 15:33:03,233 DEBUG: Done: Classification
+2016-08-24 15:33:03,754 DEBUG: Start: Statistic Results
+2016-08-24 15:33:03,754 DEBUG: Info: Classification report:
+2016-08-24 15:33:03,755 DEBUG:
+ precision recall f1-score support
+
+ Non 0.97 0.97 0.97 29
+ Oui 0.83 0.83 0.83 6
+
+avg / total 0.94 0.94 0.94 35
+
+2016-08-24 15:33:03,757 DEBUG: Info: Statistics:
+2016-08-24 15:33:03,764 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.942857142857
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.899425
+5 Mean of F1-Score of top 20 classes by F1-Score 0.899425
+6 Mean of F1-Score of top 30 classes by F1-Score 0.899425
+2016-08-24 15:33:03,764 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:33:04,063 DEBUG: Done: Statistic Results
+2016-08-24 15:33:04,064 DEBUG: Start: Plot Result
+2016-08-24 15:33:04,789 DEBUG: Done: Plot Result
+2016-08-24 15:33:04,798 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:33:04,799 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 15:33:04,799 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:33:04,812 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:33:04,812 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:33:04,813 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:33:04,813 DEBUG: Start: Classification
+2016-08-24 15:33:13,668 DEBUG: Info: Time for Classification: 8.86640405655[s]
+2016-08-24 15:33:13,668 DEBUG: Done: Classification
+2016-08-24 15:33:13,686 DEBUG: Start: Statistic Results
+2016-08-24 15:33:13,687 DEBUG: Info: Classification report:
+2016-08-24 15:33:13,688 DEBUG:
+ precision recall f1-score support
+
+ Non 0.96 0.92 0.94 26
+ Oui 0.80 0.89 0.84 9
+
+avg / total 0.92 0.91 0.92 35
+
+2016-08-24 15:33:13,689 DEBUG: Info: Statistics:
+2016-08-24 15:33:13,697 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.914285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.891641
+5 Mean of F1-Score of top 20 classes by F1-Score 0.891641
+6 Mean of F1-Score of top 30 classes by F1-Score 0.891641
+2016-08-24 15:33:13,697 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:33:14,000 DEBUG: Done: Statistic Results
+2016-08-24 15:33:14,000 DEBUG: Start: Plot Result
+2016-08-24 15:33:14,230 DEBUG: Done: Plot Result
+2016-08-24 15:33:14,239 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:33:14,240 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SGD
+2016-08-24 15:33:14,240 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:33:14,254 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:33:14,254 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:33:14,254 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:33:14,254 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-153513-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-153513-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..647aeee4c93fabac98536cb39057319e90b46f8c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-153513-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,463 @@
+2016-08-24 15:35:13,860 INFO: Begginging
+2016-08-24 15:35:13,873 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:35:13,873 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:35:13,873 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:35:13,888 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:35:13,888 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:35:13,888 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:35:13,888 DEBUG: Start: Classification
+2016-08-24 15:35:20,736 DEBUG: Info: Time for Classification: 6.85920500755[s]
+2016-08-24 15:35:20,736 DEBUG: Done: Classification
+2016-08-24 15:35:20,739 DEBUG: Start: Statistic Results
+2016-08-24 15:35:20,740 DEBUG: Info: Classification report:
+2016-08-24 15:35:20,740 DEBUG:
+ precision recall f1-score support
+
+ Non 0.92 0.79 0.85 28
+ Oui 0.45 0.71 0.56 7
+
+avg / total 0.82 0.77 0.79 35
+
+2016-08-24 15:35:20,743 DEBUG: Info: Statistics:
+2016-08-24 15:35:20,750 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.771428571429
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.700855
+5 Mean of F1-Score of top 20 classes by F1-Score 0.700855
+6 Mean of F1-Score of top 30 classes by F1-Score 0.700855
+2016-08-24 15:35:20,750 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:35:21,134 DEBUG: Done: Statistic Results
+2016-08-24 15:35:21,134 DEBUG: Start: Plot Result
+2016-08-24 15:35:21,349 DEBUG: Done: Plot Result
+2016-08-24 15:35:21,361 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:35:21,362 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 15:35:21,362 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:35:21,376 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:35:21,376 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:35:21,376 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:35:21,376 DEBUG: Start: Classification
+2016-08-24 15:35:31,289 DEBUG: Info: Time for Classification: 9.92338085175[s]
+2016-08-24 15:35:31,289 DEBUG: Done: Classification
+2016-08-24 15:35:31,806 DEBUG: Start: Statistic Results
+2016-08-24 15:35:31,806 DEBUG: Info: Classification report:
+2016-08-24 15:35:31,807 DEBUG:
+ precision recall f1-score support
+
+ Non 0.90 0.79 0.84 24
+ Oui 0.64 0.82 0.72 11
+
+avg / total 0.82 0.80 0.81 35
+
+2016-08-24 15:35:31,809 DEBUG: Info: Statistics:
+2016-08-24 15:35:31,816 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.782222
+5 Mean of F1-Score of top 20 classes by F1-Score 0.782222
+6 Mean of F1-Score of top 30 classes by F1-Score 0.782222
+2016-08-24 15:35:31,816 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:35:32,102 DEBUG: Done: Statistic Results
+2016-08-24 15:35:32,102 DEBUG: Start: Plot Result
+2016-08-24 15:35:32,829 DEBUG: Done: Plot Result
+2016-08-24 15:35:32,839 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:35:32,839 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 15:35:32,839 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:35:32,853 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:35:32,853 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:35:32,853 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:35:32,853 DEBUG: Start: Classification
+2016-08-24 15:35:40,098 DEBUG: Info: Time for Classification: 7.25602412224[s]
+2016-08-24 15:35:40,099 DEBUG: Done: Classification
+2016-08-24 15:35:40,107 DEBUG: Start: Statistic Results
+2016-08-24 15:35:40,108 DEBUG: Info: Classification report:
+2016-08-24 15:35:40,108 DEBUG:
+ precision recall f1-score support
+
+ Non 1.00 0.93 0.97 30
+ Oui 0.71 1.00 0.83 5
+
+avg / total 0.96 0.94 0.95 35
+
+2016-08-24 15:35:40,110 DEBUG: Info: Statistics:
+2016-08-24 15:35:40,118 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.942857142857
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.899425
+5 Mean of F1-Score of top 20 classes by F1-Score 0.899425
+6 Mean of F1-Score of top 30 classes by F1-Score 0.899425
+2016-08-24 15:35:40,118 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:35:40,419 DEBUG: Done: Statistic Results
+2016-08-24 15:35:40,419 DEBUG: Start: Plot Result
+2016-08-24 15:35:40,641 DEBUG: Done: Plot Result
+2016-08-24 15:35:40,650 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:35:40,650 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SGD
+2016-08-24 15:35:40,651 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:35:40,664 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:35:40,664 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:35:40,665 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:35:40,665 DEBUG: Start: Classification
+2016-08-24 15:35:42,133 DEBUG: Info: Time for Classification: 1.47857999802[s]
+2016-08-24 15:35:42,133 DEBUG: Done: Classification
+2016-08-24 15:35:42,157 DEBUG: Start: Statistic Results
+2016-08-24 15:35:42,157 DEBUG: Info: Classification report:
+2016-08-24 15:35:42,159 DEBUG:
+ precision recall f1-score support
+
+ Non 0.96 0.86 0.91 29
+ Oui 0.56 0.83 0.67 6
+
+avg / total 0.89 0.86 0.87 35
+
+2016-08-24 15:35:42,162 DEBUG: Info: Statistics:
+2016-08-24 15:35:42,176 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.857142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.787879
+5 Mean of F1-Score of top 20 classes by F1-Score 0.787879
+6 Mean of F1-Score of top 30 classes by F1-Score 0.787879
+2016-08-24 15:35:42,176 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:35:42,575 DEBUG: Done: Statistic Results
+2016-08-24 15:35:42,576 DEBUG: Start: Plot Result
+2016-08-24 15:35:42,919 DEBUG: Done: Plot Result
+2016-08-24 15:35:42,931 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:35:42,932 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMLinear
+2016-08-24 15:35:42,932 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:35:42,952 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:35:42,952 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:35:42,952 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:35:42,952 DEBUG: Start: Classification
+2016-08-24 15:35:50,958 DEBUG: Info: Time for Classification: 8.02294683456[s]
+2016-08-24 15:35:50,958 DEBUG: Done: Classification
+2016-08-24 15:35:51,120 DEBUG: Start: Statistic Results
+2016-08-24 15:35:51,120 DEBUG: Info: Classification report:
+2016-08-24 15:35:51,121 DEBUG:
+ precision recall f1-score support
+
+ Non 0.97 0.90 0.93 31
+ Oui 0.50 0.75 0.60 4
+
+avg / total 0.91 0.89 0.90 35
+
+2016-08-24 15:35:51,123 DEBUG: Info: Statistics:
+2016-08-24 15:35:51,130 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.885714285714
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.766667
+5 Mean of F1-Score of top 20 classes by F1-Score 0.766667
+6 Mean of F1-Score of top 30 classes by F1-Score 0.766667
+2016-08-24 15:35:51,130 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:35:51,433 DEBUG: Done: Statistic Results
+2016-08-24 15:35:51,433 DEBUG: Start: Plot Result
+2016-08-24 15:35:51,806 DEBUG: Done: Plot Result
+2016-08-24 15:35:51,816 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:35:51,816 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMRBF
+2016-08-24 15:35:51,816 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:35:51,830 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 15:35:51,830 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 15:35:51,830 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:35:51,830 DEBUG: Start: Classification
+2016-08-24 15:35:59,691 DEBUG: Info: Time for Classification: 7.87138581276[s]
+2016-08-24 15:35:59,691 DEBUG: Done: Classification
+2016-08-24 15:35:59,853 DEBUG: Start: Statistic Results
+2016-08-24 15:35:59,853 DEBUG: Info: Classification report:
+2016-08-24 15:35:59,854 DEBUG:
+ precision recall f1-score support
+
+ Non 0.87 0.91 0.89 22
+ Oui 0.83 0.77 0.80 13
+
+avg / total 0.86 0.86 0.86 35
+
+2016-08-24 15:35:59,856 DEBUG: Info: Statistics:
+2016-08-24 15:35:59,863 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.857142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.844444
+5 Mean of F1-Score of top 20 classes by F1-Score 0.844444
+6 Mean of F1-Score of top 30 classes by F1-Score 0.844444
+2016-08-24 15:35:59,863 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:00,167 DEBUG: Done: Statistic Results
+2016-08-24 15:36:00,167 DEBUG: Start: Plot Result
+2016-08-24 15:36:00,556 DEBUG: Done: Plot Result
+2016-08-24 15:36:00,590 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:00,590 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:36:00,590 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:00,591 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 15:36:00,591 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 15:36:00,591 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:00,591 DEBUG: Start: Classification
+2016-08-24 15:36:00,792 DEBUG: Info: Time for Classification: 0.19925403595[s]
+2016-08-24 15:36:00,792 DEBUG: Done: Classification
+2016-08-24 15:36:00,794 DEBUG: Start: Statistic Results
+2016-08-24 15:36:00,794 DEBUG: Info: Classification report:
+2016-08-24 15:36:00,795 DEBUG:
+ precision recall f1-score support
+
+ Non 0.81 0.92 0.86 24
+ Oui 0.75 0.55 0.63 11
+
+avg / total 0.79 0.80 0.79 35
+
+2016-08-24 15:36:00,797 DEBUG: Info: Statistics:
+2016-08-24 15:36:00,804 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.747162
+5 Mean of F1-Score of top 20 classes by F1-Score 0.747162
+6 Mean of F1-Score of top 30 classes by F1-Score 0.747162
+2016-08-24 15:36:00,804 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:01,103 DEBUG: Done: Statistic Results
+2016-08-24 15:36:01,103 DEBUG: Start: Plot Result
+2016-08-24 15:36:01,325 DEBUG: Done: Plot Result
+2016-08-24 15:36:01,326 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:01,326 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 15:36:01,327 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:01,327 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 15:36:01,327 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 15:36:01,327 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:01,328 DEBUG: Start: Classification
+2016-08-24 15:36:01,694 DEBUG: Info: Time for Classification: 0.363206863403[s]
+2016-08-24 15:36:01,694 DEBUG: Done: Classification
+2016-08-24 15:36:01,714 DEBUG: Start: Statistic Results
+2016-08-24 15:36:01,715 DEBUG: Info: Classification report:
+2016-08-24 15:36:01,716 DEBUG:
+ precision recall f1-score support
+
+ Non 0.96 0.96 0.96 27
+ Oui 0.88 0.88 0.88 8
+
+avg / total 0.94 0.94 0.94 35
+
+2016-08-24 15:36:01,720 DEBUG: Info: Statistics:
+2016-08-24 15:36:01,731 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.942857142857
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.918981
+5 Mean of F1-Score of top 20 classes by F1-Score 0.918981
+6 Mean of F1-Score of top 30 classes by F1-Score 0.918981
+2016-08-24 15:36:01,732 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:02,044 DEBUG: Done: Statistic Results
+2016-08-24 15:36:02,044 DEBUG: Start: Plot Result
+2016-08-24 15:36:02,331 DEBUG: Done: Plot Result
+2016-08-24 15:36:02,332 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:02,332 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 15:36:02,333 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:02,333 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 15:36:02,333 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 15:36:02,333 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:02,334 DEBUG: Start: Classification
+2016-08-24 15:36:04,885 DEBUG: Info: Time for Classification: 2.54951691628[s]
+2016-08-24 15:36:04,885 DEBUG: Done: Classification
+2016-08-24 15:36:04,889 DEBUG: Start: Statistic Results
+2016-08-24 15:36:04,889 DEBUG: Info: Classification report:
+2016-08-24 15:36:04,890 DEBUG:
+ precision recall f1-score support
+
+ Non 0.93 0.97 0.95 29
+ Oui 0.80 0.67 0.73 6
+
+avg / total 0.91 0.91 0.91 35
+
+2016-08-24 15:36:04,892 DEBUG: Info: Statistics:
+2016-08-24 15:36:04,900 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.914285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.838213
+5 Mean of F1-Score of top 20 classes by F1-Score 0.838213
+6 Mean of F1-Score of top 30 classes by F1-Score 0.838213
+2016-08-24 15:36:04,900 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:05,213 DEBUG: Done: Statistic Results
+2016-08-24 15:36:05,213 DEBUG: Start: Plot Result
+2016-08-24 15:36:05,434 DEBUG: Done: Plot Result
+2016-08-24 15:36:05,435 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:05,435 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SGD
+2016-08-24 15:36:05,435 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:05,436 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 15:36:05,436 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 15:36:05,436 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:05,436 DEBUG: Start: Classification
+2016-08-24 15:36:05,523 DEBUG: Info: Time for Classification: 0.0844321250916[s]
+2016-08-24 15:36:05,523 DEBUG: Done: Classification
+2016-08-24 15:36:05,525 DEBUG: Start: Statistic Results
+2016-08-24 15:36:05,525 DEBUG: Info: Classification report:
+2016-08-24 15:36:05,526 DEBUG:
+ precision recall f1-score support
+
+ Non 1.00 0.60 0.75 25
+ Oui 0.50 1.00 0.67 10
+
+avg / total 0.86 0.71 0.73 35
+
+2016-08-24 15:36:05,528 DEBUG: Info: Statistics:
+2016-08-24 15:36:05,536 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.708333
+5 Mean of F1-Score of top 20 classes by F1-Score 0.708333
+6 Mean of F1-Score of top 30 classes by F1-Score 0.708333
+2016-08-24 15:36:05,536 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:05,859 DEBUG: Done: Statistic Results
+2016-08-24 15:36:05,859 DEBUG: Start: Plot Result
+2016-08-24 15:36:06,199 DEBUG: Done: Plot Result
+2016-08-24 15:36:06,200 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:06,201 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMLinear
+2016-08-24 15:36:06,201 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:06,201 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 15:36:06,201 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 15:36:06,202 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:06,202 DEBUG: Start: Classification
+2016-08-24 15:36:11,831 DEBUG: Info: Time for Classification: 5.62734603882[s]
+2016-08-24 15:36:11,831 DEBUG: Done: Classification
+2016-08-24 15:36:11,836 DEBUG: Start: Statistic Results
+2016-08-24 15:36:11,836 DEBUG: Info: Classification report:
+2016-08-24 15:36:11,837 DEBUG:
+ precision recall f1-score support
+
+ Non 0.92 0.73 0.81 30
+ Oui 0.27 0.60 0.37 5
+
+avg / total 0.82 0.71 0.75 35
+
+2016-08-24 15:36:11,839 DEBUG: Info: Statistics:
+2016-08-24 15:36:11,846 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.594907
+5 Mean of F1-Score of top 20 classes by F1-Score 0.594907
+6 Mean of F1-Score of top 30 classes by F1-Score 0.594907
+2016-08-24 15:36:11,846 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:12,215 DEBUG: Done: Statistic Results
+2016-08-24 15:36:12,215 DEBUG: Start: Plot Result
+2016-08-24 15:36:12,479 DEBUG: Done: Plot Result
+2016-08-24 15:36:12,480 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:12,480 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMRBF
+2016-08-24 15:36:12,480 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:12,481 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 15:36:12,481 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 15:36:12,481 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:12,481 DEBUG: Start: Classification
+2016-08-24 15:36:13,146 DEBUG: Info: Time for Classification: 0.662354946136[s]
+2016-08-24 15:36:13,146 DEBUG: Done: Classification
+2016-08-24 15:36:13,161 DEBUG: Start: Statistic Results
+2016-08-24 15:36:13,162 DEBUG: Info: Classification report:
+2016-08-24 15:36:13,185 DEBUG:
+ precision recall f1-score support
+
+ Non 0.71 1.00 0.83 25
+ Oui 0.00 0.00 0.00 10
+
+avg / total 0.51 0.71 0.60 35
+
+2016-08-24 15:36:13,187 DEBUG: Info: Statistics:
+2016-08-24 15:36:13,195 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.416667
+5 Mean of F1-Score of top 20 classes by F1-Score 0.416667
+6 Mean of F1-Score of top 30 classes by F1-Score 0.416667
+2016-08-24 15:36:13,195 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:13,572 DEBUG: Done: Statistic Results
+2016-08-24 15:36:13,572 DEBUG: Start: Plot Result
+2016-08-24 15:36:13,826 DEBUG: Done: Plot Result
+2016-08-24 15:36:14,979 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:14,979 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 15:36:14,979 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:15,063 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 15:36:15,063 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 15:36:15,063 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:15,063 DEBUG: Start: Classification
+2016-08-24 15:36:36,485 DEBUG: Info: Time for Classification: 21.5033020973[s]
+2016-08-24 15:36:36,485 DEBUG: Done: Classification
+2016-08-24 15:36:36,489 DEBUG: Start: Statistic Results
+2016-08-24 15:36:36,489 DEBUG: Info: Classification report:
+2016-08-24 15:36:36,490 DEBUG:
+ precision recall f1-score support
+
+ Non 0.66 1.00 0.79 23
+ Oui 0.00 0.00 0.00 12
+
+avg / total 0.43 0.66 0.52 35
+
+2016-08-24 15:36:36,492 DEBUG: Info: Statistics:
+2016-08-24 15:36:36,499 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.657142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.396552
+5 Mean of F1-Score of top 20 classes by F1-Score 0.396552
+6 Mean of F1-Score of top 30 classes by F1-Score 0.396552
+2016-08-24 15:36:36,500 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:36:36,817 DEBUG: Done: Statistic Results
+2016-08-24 15:36:36,818 DEBUG: Start: Plot Result
+2016-08-24 15:36:37,036 DEBUG: Done: Plot Result
+2016-08-24 15:36:38,028 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 15:36:38,028 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 15:36:38,028 DEBUG: Start: Determine Train/Test split
+2016-08-24 15:36:38,080 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 15:36:38,080 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 15:36:38,080 DEBUG: Done: Determine Train/Test split
+2016-08-24 15:36:38,080 DEBUG: Start: Classification
+2016-08-24 15:37:07,285 DEBUG: Info: Time for Classification: 28.5032260418[s]
+2016-08-24 15:37:07,285 DEBUG: Done: Classification
+2016-08-24 15:37:08,833 DEBUG: Start: Statistic Results
+2016-08-24 15:37:08,834 DEBUG: Info: Classification report:
+2016-08-24 15:37:08,920 DEBUG:
+ precision recall f1-score support
+
+ Non 0.74 0.96 0.83 26
+ Oui 0.00 0.00 0.00 9
+
+avg / total 0.55 0.71 0.62 35
+
+2016-08-24 15:37:08,954 DEBUG: Info: Statistics:
+2016-08-24 15:37:09,007 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.416667
+5 Mean of F1-Score of top 20 classes by F1-Score 0.416667
+6 Mean of F1-Score of top 30 classes by F1-Score 0.416667
+2016-08-24 15:37:09,007 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 15:37:12,867 DEBUG: Done: Statistic Results
+2016-08-24 15:37:12,867 DEBUG: Start: Plot Result
+2016-08-24 15:37:14,530 DEBUG: Done: Plot Result
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-165838-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-165838-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..b4b31aa895c5e3a10bab4af9755f3b73a41b39db
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-165838-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1 @@
+2016-08-24 16:58:38,944 INFO: Begginging
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170101-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170101-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..ab433508bd0d420b7d299e3cbc03dfa74afe0703
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170101-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1 @@
+2016-08-24 17:01:01,205 INFO: Begginging
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170131-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170131-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..132c798c184f22e6ce1c5ecd293090c2bbae525f
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170131-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1 @@
+2016-08-24 17:01:31,670 INFO: Begginging
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170148-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170148-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..aa4df084e6c3db2a516aff2d1668b3dda351b1b2
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170148-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,24 @@
+2016-08-24 17:01:48,282 INFO: Begginging
+2016-08-24 17:01:48,285 INFO: ### Main Programm for Multiview Classification
+2016-08-24 17:01:48,285 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 17:01:48,285 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-24 17:01:48,285 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-24 17:01:48,286 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-24 17:01:48,286 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-24 17:01:48,286 INFO: Done: Read Database Files
+2016-08-24 17:01:48,287 INFO: Start: Determine validation split for ratio 0.9
+2016-08-24 17:01:48,309 INFO: Done: Determine validation split
+2016-08-24 17:01:48,310 INFO: Start: Determine 2 folds
+2016-08-24 17:01:48,328 INFO: Info: Length of Learning Sets: 157
+2016-08-24 17:01:48,328 INFO: Info: Length of Testing Sets: 156
+2016-08-24 17:01:48,328 INFO: Info: Length of Validation Set: 34
+2016-08-24 17:01:48,328 INFO: Done: Determine folds
+2016-08-24 17:01:48,328 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 17:01:48,328 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 17:01:48,329 DEBUG: Start: Gridsearch for DecisionTree on Methyl
+2016-08-24 17:01:56,163 DEBUG: Info: Best Reslut : 0.542708933718
+2016-08-24 17:01:56,163 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:01:56,164 DEBUG: Start: Gridsearch for DecisionTree on MiRNA_
+2016-08-24 17:01:58,267 DEBUG: Info: Best Reslut : 0.553948126801
+2016-08-24 17:01:58,267 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:01:58,267 DEBUG: Start: Gridsearch for DecisionTree on RANSeq
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170204-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170204-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..3ad1a6bd81d6127939b2305b2508421cd46b89bf
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170204-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,31 @@
+2016-08-24 17:02:04,433 INFO: Begginging
+2016-08-24 17:02:04,435 INFO: ### Main Programm for Multiview Classification
+2016-08-24 17:02:04,435 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 17:02:04,435 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-24 17:02:04,436 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-24 17:02:04,436 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-24 17:02:04,437 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-24 17:02:04,437 INFO: Done: Read Database Files
+2016-08-24 17:02:04,437 INFO: Start: Determine validation split for ratio 0.9
+2016-08-24 17:02:04,440 INFO: Done: Determine validation split
+2016-08-24 17:02:04,440 INFO: Start: Determine 2 folds
+2016-08-24 17:02:04,452 INFO: Info: Length of Learning Sets: 157
+2016-08-24 17:02:04,452 INFO: Info: Length of Testing Sets: 156
+2016-08-24 17:02:04,452 INFO: Info: Length of Validation Set: 34
+2016-08-24 17:02:04,452 INFO: Done: Determine folds
+2016-08-24 17:02:04,452 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 17:02:04,452 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 17:02:04,453 DEBUG: Start: Gridsearch for DecisionTree on Methyl
+2016-08-24 17:02:11,934 DEBUG: Info: Best Reslut : 0.550489913545
+2016-08-24 17:02:11,934 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:02:11,935 DEBUG: Start: Gridsearch for DecisionTree on MiRNA_
+2016-08-24 17:02:13,994 DEBUG: Info: Best Reslut : 0.560345821326
+2016-08-24 17:02:13,994 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:02:13,994 DEBUG: Start: Gridsearch for DecisionTree on RANSeq
+2016-08-24 17:02:30,869 DEBUG: Info: Best Reslut : 0.512507204611
+2016-08-24 17:02:30,869 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:02:30,870 DEBUG: Start: Gridsearch for DecisionTree on Clinic
+2016-08-24 17:02:32,818 DEBUG: Info: Best Reslut : 0.506109510086
+2016-08-24 17:02:32,819 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:02:32,819 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 17:02:32,819 INFO: Start: Fold number 1
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170346-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170346-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..e95f7dd37b0173564895d137b8480cc96a582e33
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170346-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,150 @@
+2016-08-24 17:03:46,119 INFO: Begginging
+2016-08-24 17:03:46,120 INFO: ### Main Programm for Multiview Classification
+2016-08-24 17:03:46,121 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 17:03:46,121 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-24 17:03:46,121 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-24 17:03:46,122 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-24 17:03:46,122 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-24 17:03:46,122 INFO: Done: Read Database Files
+2016-08-24 17:03:46,122 INFO: Start: Determine validation split for ratio 0.9
+2016-08-24 17:03:46,125 INFO: Done: Determine validation split
+2016-08-24 17:03:46,125 INFO: Start: Determine 2 folds
+2016-08-24 17:03:46,142 INFO: Info: Length of Learning Sets: 157
+2016-08-24 17:03:46,142 INFO: Info: Length of Testing Sets: 156
+2016-08-24 17:03:46,142 INFO: Info: Length of Validation Set: 34
+2016-08-24 17:03:46,142 INFO: Done: Determine folds
+2016-08-24 17:03:46,142 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 17:03:46,142 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 17:03:46,143 DEBUG: Start: Gridsearch for DecisionTree on Methyl
+2016-08-24 17:03:53,600 DEBUG: Info: Best Reslut : 0.531123919308
+2016-08-24 17:03:53,600 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:03:53,601 DEBUG: Start: Gridsearch for DecisionTree on MiRNA_
+2016-08-24 17:03:55,659 DEBUG: Info: Best Reslut : 0.501613832853
+2016-08-24 17:03:55,659 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:03:55,660 DEBUG: Start: Gridsearch for DecisionTree on RANSeq
+2016-08-24 17:04:13,538 DEBUG: Info: Best Reslut : 0.502363112392
+2016-08-24 17:04:13,538 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:04:13,539 DEBUG: Start: Gridsearch for DecisionTree on Clinic
+2016-08-24 17:04:15,465 DEBUG: Info: Best Reslut : 0.58144092219
+2016-08-24 17:04:15,465 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:04:15,465 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 17:04:15,466 INFO: Start: Fold number 1
+2016-08-24 17:04:17,304 DEBUG: Start: Iteration 1
+2016-08-24 17:04:17,324 DEBUG: View 0 : 0.563953488372
+2016-08-24 17:04:17,333 DEBUG: View 1 : 0.703488372093
+2016-08-24 17:04:17,372 DEBUG: View 2 : 0.68023255814
+2016-08-24 17:04:17,381 DEBUG: View 3 : 0.546511627907
+2016-08-24 17:04:17,428 DEBUG: Best view : Methyl
+2016-08-24 17:04:17,511 DEBUG: Start: Iteration 2
+2016-08-24 17:04:17,529 DEBUG: View 0 : 0.546511627907
+2016-08-24 17:04:17,539 DEBUG: View 1 : 0.703488372093
+2016-08-24 17:04:17,578 DEBUG: View 2 : 0.46511627907
+2016-08-24 17:04:17,587 DEBUG: View 3 : 0.308139534884
+2016-08-24 17:04:17,645 DEBUG: Best view : MiRNA_
+2016-08-24 17:04:17,802 DEBUG: Start: Iteration 3
+2016-08-24 17:04:17,820 DEBUG: View 0 : 0.529069767442
+2016-08-24 17:04:17,829 DEBUG: View 1 : 0.43023255814
+2016-08-24 17:04:17,869 DEBUG: View 2 : 0.377906976744
+2016-08-24 17:04:17,878 DEBUG: View 3 : 0.389534883721
+2016-08-24 17:04:17,937 DEBUG: Best view : Methyl
+2016-08-24 17:04:18,161 DEBUG: Start: Iteration 4
+2016-08-24 17:04:18,180 DEBUG: View 0 : 0.697674418605
+2016-08-24 17:04:18,189 DEBUG: View 1 : 0.337209302326
+2016-08-24 17:04:18,228 DEBUG: View 2 : 0.604651162791
+2016-08-24 17:04:18,237 DEBUG: View 3 : 0.604651162791
+2016-08-24 17:04:18,300 DEBUG: Best view : Methyl
+2016-08-24 17:04:18,594 DEBUG: Start: Iteration 5
+2016-08-24 17:04:18,612 DEBUG: View 0 : 0.656976744186
+2016-08-24 17:04:18,621 DEBUG: View 1 : 0.424418604651
+2016-08-24 17:04:18,660 DEBUG: View 2 : 0.43023255814
+2016-08-24 17:04:18,669 DEBUG: View 3 : 0.674418604651
+2016-08-24 17:04:18,734 DEBUG: Best view : Methyl
+2016-08-24 17:04:19,088 DEBUG: Start: Iteration 6
+2016-08-24 17:04:19,106 DEBUG: View 0 : 0.593023255814
+2016-08-24 17:04:19,114 DEBUG: View 1 : 0.610465116279
+2016-08-24 17:04:19,153 DEBUG: View 2 : 0.360465116279
+2016-08-24 17:04:19,162 DEBUG: View 3 : 0.372093023256
+2016-08-24 17:04:19,231 DEBUG: Best view : MiRNA_
+2016-08-24 17:04:19,648 DEBUG: Start: Iteration 7
+2016-08-24 17:04:19,666 DEBUG: View 0 : 0.523255813953
+2016-08-24 17:04:19,675 DEBUG: View 1 : 0.709302325581
+2016-08-24 17:04:19,714 DEBUG: View 2 : 0.418604651163
+2016-08-24 17:04:19,723 DEBUG: View 3 : 0.406976744186
+2016-08-24 17:04:19,795 DEBUG: Best view : MiRNA_
+2016-08-24 17:04:20,275 DEBUG: Start: Iteration 8
+2016-08-24 17:04:20,293 DEBUG: View 0 : 0.78488372093
+2016-08-24 17:04:20,302 DEBUG: View 1 : 0.593023255814
+2016-08-24 17:04:20,342 DEBUG: View 2 : 0.540697674419
+2016-08-24 17:04:20,350 DEBUG: View 3 : 0.639534883721
+2016-08-24 17:04:20,425 DEBUG: Best view : Methyl
+2016-08-24 17:04:20,980 DEBUG: Start: Iteration 9
+2016-08-24 17:04:20,998 DEBUG: View 0 : 0.31976744186
+2016-08-24 17:04:21,007 DEBUG: View 1 : 0.796511627907
+2016-08-24 17:04:21,046 DEBUG: View 2 : 0.610465116279
+2016-08-24 17:04:21,055 DEBUG: View 3 : 0.656976744186
+2016-08-24 17:04:21,131 DEBUG: Best view : MiRNA_
+2016-08-24 17:04:21,741 DEBUG: Start: Iteration 10
+2016-08-24 17:04:21,758 DEBUG: View 0 : 0.476744186047
+2016-08-24 17:04:21,767 DEBUG: View 1 : 0.354651162791
+2016-08-24 17:04:21,807 DEBUG: View 2 : 0.505813953488
+2016-08-24 17:04:21,816 DEBUG: View 3 : 0.5
+2016-08-24 17:04:21,894 DEBUG: Best view : Methyl
+2016-08-24 17:04:22,579 DEBUG: Start: Iteration 11
+2016-08-24 17:04:22,597 DEBUG: View 0 : 0.575581395349
+2016-08-24 17:04:22,606 DEBUG: View 1 : 0.354651162791
+2016-08-24 17:04:22,645 DEBUG: View 2 : 0.552325581395
+2016-08-24 17:04:22,653 DEBUG: View 3 : 0.418604651163
+2016-08-24 17:04:22,736 DEBUG: Best view : Methyl
+2016-08-24 17:04:23,491 DEBUG: Start: Iteration 12
+2016-08-24 17:04:23,509 DEBUG: View 0 : 0.488372093023
+2016-08-24 17:04:23,518 DEBUG: View 1 : 0.633720930233
+2016-08-24 17:04:23,556 DEBUG: View 2 : 0.616279069767
+2016-08-24 17:04:23,565 DEBUG: View 3 : 0.395348837209
+2016-08-24 17:04:23,650 DEBUG: Best view : MiRNA_
+2016-08-24 17:04:24,460 DEBUG: Start: Iteration 13
+2016-08-24 17:04:24,478 DEBUG: View 0 : 0.436046511628
+2016-08-24 17:04:24,487 DEBUG: View 1 : 0.627906976744
+2016-08-24 17:04:24,525 DEBUG: View 2 : 0.581395348837
+2016-08-24 17:04:24,534 DEBUG: View 3 : 0.488372093023
+2016-08-24 17:04:24,621 DEBUG: Best view : MiRNA_
+2016-08-24 17:04:25,498 DEBUG: Start: Iteration 14
+2016-08-24 17:04:25,516 DEBUG: View 0 : 0.738372093023
+2016-08-24 17:04:25,525 DEBUG: View 1 : 0.662790697674
+2016-08-24 17:04:25,564 DEBUG: View 2 : 0.46511627907
+2016-08-24 17:04:25,572 DEBUG: View 3 : 0.412790697674
+2016-08-24 17:04:25,662 DEBUG: Best view : Methyl
+2016-08-24 17:04:26,603 DEBUG: Start: Iteration 15
+2016-08-24 17:04:26,621 DEBUG: View 0 : 0.56976744186
+2016-08-24 17:04:26,629 DEBUG: View 1 : 0.308139534884
+2016-08-24 17:04:26,668 DEBUG: View 2 : 0.453488372093
+2016-08-24 17:04:26,676 DEBUG: View 3 : 0.418604651163
+2016-08-24 17:04:26,769 DEBUG: Best view : Methyl
+2016-08-24 17:04:27,796 DEBUG: Start: Iteration 16
+2016-08-24 17:04:27,816 DEBUG: View 0 : 0.436046511628
+2016-08-24 17:04:27,826 DEBUG: View 1 : 0.761627906977
+2016-08-24 17:04:27,866 DEBUG: View 2 : 0.668604651163
+2016-08-24 17:04:27,875 DEBUG: View 3 : 0.505813953488
+2016-08-24 17:04:27,978 DEBUG: Best view : MiRNA_
+2016-08-24 17:04:29,101 DEBUG: Start: Iteration 17
+2016-08-24 17:04:29,120 DEBUG: View 0 : 0.31976744186
+2016-08-24 17:04:29,130 DEBUG: View 1 : 0.31976744186
+2016-08-24 17:04:29,173 DEBUG: View 2 : 0.517441860465
+2016-08-24 17:04:29,183 DEBUG: View 3 : 0.505813953488
+2016-08-24 17:04:29,333 DEBUG: Best view : RANSeq
+2016-08-24 17:04:30,588 DEBUG: Start: Iteration 18
+2016-08-24 17:04:30,607 DEBUG: View 0 : 0.616279069767
+2016-08-24 17:04:30,616 DEBUG: View 1 : 0.366279069767
+2016-08-24 17:04:30,656 DEBUG: View 2 : 0.372093023256
+2016-08-24 17:04:30,666 DEBUG: View 3 : 0.651162790698
+2016-08-24 17:04:30,786 DEBUG: Best view : Clinic
+2016-08-24 17:04:32,048 DEBUG: Start: Iteration 19
+2016-08-24 17:04:32,066 DEBUG: View 0 : 0.523255813953
+2016-08-24 17:04:32,075 DEBUG: View 1 : 0.441860465116
+2016-08-24 17:04:32,114 DEBUG: View 2 : 0.436046511628
+2016-08-24 17:04:32,123 DEBUG: View 3 : 0.470930232558
+2016-08-24 17:04:32,233 DEBUG: Best view : Methyl
+2016-08-24 17:04:33,641 DEBUG: Start: Iteration 20
+2016-08-24 17:04:33,666 DEBUG: View 0 : 0.406976744186
+2016-08-24 17:04:33,676 DEBUG: View 1 : 0.563953488372
+2016-08-24 17:04:33,723 DEBUG: View 2 : 0.46511627907
+2016-08-24 17:04:33,733 DEBUG: View 3 : 0.43023255814
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170435-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170435-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..4766a8dfc8c6d9f7ef8e4b329f6c1cb0ff3dbad5
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170435-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,18 @@
+2016-08-24 17:04:35,603 INFO: Begginging
+2016-08-24 17:04:35,606 INFO: ### Main Programm for Multiview Classification
+2016-08-24 17:04:35,606 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 17:04:35,607 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-24 17:04:35,607 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-24 17:04:35,607 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-24 17:04:35,608 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-24 17:04:35,608 INFO: Done: Read Database Files
+2016-08-24 17:04:35,608 INFO: Start: Determine validation split for ratio 0.9
+2016-08-24 17:04:35,611 INFO: Done: Determine validation split
+2016-08-24 17:04:35,611 INFO: Start: Determine 2 folds
+2016-08-24 17:04:35,627 INFO: Info: Length of Learning Sets: 157
+2016-08-24 17:04:35,627 INFO: Info: Length of Testing Sets: 156
+2016-08-24 17:04:35,627 INFO: Info: Length of Validation Set: 34
+2016-08-24 17:04:35,627 INFO: Done: Determine folds
+2016-08-24 17:04:35,627 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 17:04:35,627 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 17:04:35,627 DEBUG: Start: Gridsearch for DecisionTree on Methyl
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170504-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170504-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..f2e8de61dd36dab70d9c6499109aa4b04e29a7f4
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170504-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1 @@
+2016-08-24 17:05:04,538 INFO: Begginging
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170547-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170547-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..ed318790f510ea26b86a25cc01bf930c309d88d1
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170547-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1 @@
+2016-08-24 17:05:47,733 INFO: Begginging
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170609-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170609-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..2fd16d8239ccf91ea127fa59c977ccf9079b49bf
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170609-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 17:06:09,716 INFO: Begginging
+2016-08-24 17:06:09,729 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:06:09,729 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:06:09,729 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:06:09,742 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:06:09,743 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:06:09,743 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:06:09,743 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170651-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170651-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..921f51754fb249d0dfc7ac96c2c599a5250e1d44
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170651-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 17:06:51,976 INFO: Begginging
+2016-08-24 17:06:51,987 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:06:51,988 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:06:51,988 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:06:52,001 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:06:52,001 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:06:52,002 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:06:52,002 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170714-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170714-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..7659913c847106f6cd87c44b69a9af90736b5fec
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170714-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 17:07:14,669 INFO: Begginging
+2016-08-24 17:07:14,681 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:07:14,682 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:07:14,682 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:07:14,695 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:07:14,695 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:07:14,696 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:07:14,696 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-170830-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-170830-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..c8f73426559662169f1096b253c9b99c5120ec3c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-170830-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 17:08:30,663 INFO: Begginging
+2016-08-24 17:08:30,675 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:08:30,675 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:08:30,675 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:08:30,689 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:08:30,690 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:08:30,690 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:08:30,690 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-171109-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-171109-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..796f2ca889acd7ca90f642b8a3bb78e9f8969cd0
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-171109-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 17:11:09,644 INFO: Begginging
+2016-08-24 17:11:09,657 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:11:09,657 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:11:09,657 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:11:09,674 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:11:09,674 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:11:09,674 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:11:09,674 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-171228-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-171228-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..d1279bafe2afbb9f65af8ff8f00dd70f6880140d
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-171228-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,8 @@
+2016-08-24 17:12:28,726 INFO: Begginging
+2016-08-24 17:12:28,738 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:12:28,738 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:12:28,739 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:12:28,752 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:12:28,752 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:12:28,752 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:12:28,752 DEBUG: Start: Classification
diff --git a/Code/MonoMutliViewClassifiers/Results/20160824-171252-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log b/Code/MonoMutliViewClassifiers/Results/20160824-171252-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..f3d65d39040a83b2c1a7364b86e08066b3331b6c
--- /dev/null
+++ b/Code/MonoMutliViewClassifiers/Results/20160824-171252-CMultiV-Benchmark-Methyl_MiRNA__RNASeq_Clinic-MultiOmic-LOG.log
@@ -0,0 +1,1526 @@
+2016-08-24 17:12:52,347 INFO: Begginging
+2016-08-24 17:12:52,365 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:12:52,365 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:12:52,365 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:12:52,379 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:12:52,379 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:12:52,379 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:12:52,379 DEBUG: Start: Classification
+2016-08-24 17:13:02,249 DEBUG: Info: Time for Classification: 9.84349799156[s]
+2016-08-24 17:13:02,249 DEBUG: Done: Classification
+2016-08-24 17:13:02,283 DEBUG: Start: Statistic Results
+2016-08-24 17:13:02,284 DEBUG: Info: Classification report:
+2016-08-24 17:13:02,285 DEBUG:
+ precision recall f1-score support
+
+ Non 0.97 0.93 0.95 30
+ Oui 0.67 0.80 0.73 5
+
+avg / total 0.92 0.91 0.92 35
+
+2016-08-24 17:13:02,322 DEBUG: Info: Statistics:
+2016-08-24 17:13:02,330 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.914285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.838213
+5 Mean of F1-Score of top 20 classes by F1-Score 0.838213
+6 Mean of F1-Score of top 30 classes by F1-Score 0.838213
+2016-08-24 17:13:02,330 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:13:04,158 DEBUG: Done: Statistic Results
+2016-08-24 17:13:04,158 DEBUG: Start: Plot Result
+2016-08-24 17:13:04,385 DEBUG: Done: Plot Result
+2016-08-24 17:13:04,396 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:13:04,396 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 17:13:04,397 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:13:04,409 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:13:04,409 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:13:04,409 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:13:04,409 DEBUG: Start: Classification
+2016-08-24 17:13:11,488 DEBUG: Info: Time for Classification: 7.08845591545[s]
+2016-08-24 17:13:11,488 DEBUG: Done: Classification
+2016-08-24 17:13:11,490 DEBUG: Start: Statistic Results
+2016-08-24 17:13:11,490 DEBUG: Info: Classification report:
+2016-08-24 17:13:11,491 DEBUG:
+ precision recall f1-score support
+
+ Non 1.00 0.82 0.90 28
+ Oui 0.58 1.00 0.74 7
+
+avg / total 0.92 0.86 0.87 35
+
+2016-08-24 17:13:11,498 DEBUG: Info: Statistics:
+2016-08-24 17:13:11,505 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.857142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.819401
+5 Mean of F1-Score of top 20 classes by F1-Score 0.819401
+6 Mean of F1-Score of top 30 classes by F1-Score 0.819401
+2016-08-24 17:13:11,505 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:13:11,798 DEBUG: Done: Statistic Results
+2016-08-24 17:13:11,798 DEBUG: Start: Plot Result
+2016-08-24 17:13:12,021 DEBUG: Done: Plot Result
+2016-08-24 17:13:12,033 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:13:12,033 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 17:13:12,033 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:13:12,046 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:13:12,046 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:13:12,046 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:13:12,046 DEBUG: Start: Classification
+2016-08-24 17:13:21,419 DEBUG: Info: Time for Classification: 9.38218188286[s]
+2016-08-24 17:13:21,419 DEBUG: Done: Classification
+2016-08-24 17:13:21,905 DEBUG: Start: Statistic Results
+2016-08-24 17:13:21,905 DEBUG: Info: Classification report:
+2016-08-24 17:13:21,906 DEBUG:
+ precision recall f1-score support
+
+ Non 0.92 0.86 0.89 28
+ Oui 0.56 0.71 0.63 7
+
+avg / total 0.85 0.83 0.84 35
+
+2016-08-24 17:13:21,908 DEBUG: Info: Statistics:
+2016-08-24 17:13:21,915 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.828571428571
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.756944
+5 Mean of F1-Score of top 20 classes by F1-Score 0.756944
+6 Mean of F1-Score of top 30 classes by F1-Score 0.756944
+2016-08-24 17:13:21,915 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:13:22,195 DEBUG: Done: Statistic Results
+2016-08-24 17:13:22,195 DEBUG: Start: Plot Result
+2016-08-24 17:13:22,884 DEBUG: Done: Plot Result
+2016-08-24 17:13:22,892 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:13:22,892 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 17:13:22,892 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:13:22,905 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:13:22,905 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:13:22,905 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:13:22,905 DEBUG: Start: Classification
+2016-08-24 17:13:30,919 DEBUG: Info: Time for Classification: 8.02398109436[s]
+2016-08-24 17:13:30,920 DEBUG: Done: Classification
+2016-08-24 17:13:30,937 DEBUG: Start: Statistic Results
+2016-08-24 17:13:30,937 DEBUG: Info: Classification report:
+2016-08-24 17:13:30,938 DEBUG:
+ precision recall f1-score support
+
+ Non 0.91 0.80 0.85 25
+ Oui 0.62 0.80 0.70 10
+
+avg / total 0.83 0.80 0.81 35
+
+2016-08-24 17:13:30,940 DEBUG: Info: Statistics:
+2016-08-24 17:13:30,947 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.773358
+5 Mean of F1-Score of top 20 classes by F1-Score 0.773358
+6 Mean of F1-Score of top 30 classes by F1-Score 0.773358
+2016-08-24 17:13:30,947 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:13:31,246 DEBUG: Done: Statistic Results
+2016-08-24 17:13:31,246 DEBUG: Start: Plot Result
+2016-08-24 17:13:31,467 DEBUG: Done: Plot Result
+2016-08-24 17:13:31,475 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:13:31,475 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SGD
+2016-08-24 17:13:31,475 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:13:31,488 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:13:31,488 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:13:31,488 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:13:31,488 DEBUG: Start: Classification
+2016-08-24 17:13:32,881 DEBUG: Info: Time for Classification: 1.40213799477[s]
+2016-08-24 17:13:32,881 DEBUG: Done: Classification
+2016-08-24 17:13:32,898 DEBUG: Start: Statistic Results
+2016-08-24 17:13:32,899 DEBUG: Info: Classification report:
+2016-08-24 17:13:32,900 DEBUG:
+ precision recall f1-score support
+
+ Non 1.00 0.67 0.80 27
+ Oui 0.47 1.00 0.64 8
+
+avg / total 0.88 0.74 0.76 35
+
+2016-08-24 17:13:32,902 DEBUG: Info: Statistics:
+2016-08-24 17:13:32,911 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.742857142857
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.72
+5 Mean of F1-Score of top 20 classes by F1-Score 0.72
+6 Mean of F1-Score of top 30 classes by F1-Score 0.72
+2016-08-24 17:13:32,912 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:13:33,221 DEBUG: Done: Statistic Results
+2016-08-24 17:13:33,221 DEBUG: Start: Plot Result
+2016-08-24 17:13:33,508 DEBUG: Done: Plot Result
+2016-08-24 17:13:33,518 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:13:33,518 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMLinear
+2016-08-24 17:13:33,518 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:13:33,532 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:13:33,532 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:13:33,532 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:13:33,533 DEBUG: Start: Classification
+2016-08-24 17:13:40,859 DEBUG: Info: Time for Classification: 7.33764505386[s]
+2016-08-24 17:13:40,859 DEBUG: Done: Classification
+2016-08-24 17:13:40,998 DEBUG: Start: Statistic Results
+2016-08-24 17:13:40,998 DEBUG: Info: Classification report:
+2016-08-24 17:13:40,999 DEBUG:
+ precision recall f1-score support
+
+ Non 0.80 1.00 0.89 24
+ Oui 1.00 0.45 0.62 11
+
+avg / total 0.86 0.83 0.81 35
+
+2016-08-24 17:13:41,001 DEBUG: Info: Statistics:
+2016-08-24 17:13:41,008 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.828571428571
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.756944
+5 Mean of F1-Score of top 20 classes by F1-Score 0.756944
+6 Mean of F1-Score of top 30 classes by F1-Score 0.756944
+2016-08-24 17:13:41,008 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:13:41,289 DEBUG: Done: Statistic Results
+2016-08-24 17:13:41,289 DEBUG: Start: Plot Result
+2016-08-24 17:13:41,642 DEBUG: Done: Plot Result
+2016-08-24 17:13:41,650 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:13:41,650 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMPoly
+2016-08-24 17:13:41,650 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:13:41,663 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:13:41,663 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:13:41,663 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:13:41,663 DEBUG: Start: Classification
+2016-08-24 17:14:06,809 DEBUG: Info: Time for Classification: 25.1557309628[s]
+2016-08-24 17:14:06,809 DEBUG: Done: Classification
+2016-08-24 17:14:06,949 DEBUG: Start: Statistic Results
+2016-08-24 17:14:06,949 DEBUG: Info: Classification report:
+2016-08-24 17:14:06,950 DEBUG:
+ precision recall f1-score support
+
+ Non 0.88 0.92 0.90 25
+ Oui 0.78 0.70 0.74 10
+
+avg / total 0.85 0.86 0.85 35
+
+2016-08-24 17:14:06,952 DEBUG: Info: Statistics:
+2016-08-24 17:14:06,959 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.857142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.819401
+5 Mean of F1-Score of top 20 classes by F1-Score 0.819401
+6 Mean of F1-Score of top 30 classes by F1-Score 0.819401
+2016-08-24 17:14:06,959 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:07,241 DEBUG: Done: Statistic Results
+2016-08-24 17:14:07,241 DEBUG: Start: Plot Result
+2016-08-24 17:14:07,583 DEBUG: Done: Plot Result
+2016-08-24 17:14:07,591 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:07,592 DEBUG: ### Classification - Database:MultiOmic Feature:MiRNA_ train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMRBF
+2016-08-24 17:14:07,592 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:07,605 DEBUG: Info: Shape X_train:(312, 25978), Length of y_train:312
+2016-08-24 17:14:07,605 DEBUG: Info: Shape X_test:(35, 25978), Length of y_test:35
+2016-08-24 17:14:07,605 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:07,605 DEBUG: Start: Classification
+2016-08-24 17:14:15,024 DEBUG: Info: Time for Classification: 7.42890310287[s]
+2016-08-24 17:14:15,024 DEBUG: Done: Classification
+2016-08-24 17:14:15,163 DEBUG: Start: Statistic Results
+2016-08-24 17:14:15,163 DEBUG: Info: Classification report:
+2016-08-24 17:14:15,164 DEBUG:
+ precision recall f1-score support
+
+ Non 1.00 0.97 0.98 29
+ Oui 0.86 1.00 0.92 6
+
+avg / total 0.98 0.97 0.97 35
+
+2016-08-24 17:14:15,165 DEBUG: Info: Statistics:
+2016-08-24 17:14:15,172 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.971428571429
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.952767
+5 Mean of F1-Score of top 20 classes by F1-Score 0.952767
+6 Mean of F1-Score of top 30 classes by F1-Score 0.952767
+2016-08-24 17:14:15,172 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:15,325 DEBUG: Done: Statistic Results
+2016-08-24 17:14:15,325 DEBUG: Start: Plot Result
+2016-08-24 17:14:15,573 DEBUG: Done: Plot Result
+2016-08-24 17:14:15,575 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:15,575 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:14:15,575 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:15,576 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:15,576 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:15,576 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:15,576 DEBUG: Start: Classification
+2016-08-24 17:14:15,863 DEBUG: Info: Time for Classification: 0.284190177917[s]
+2016-08-24 17:14:15,863 DEBUG: Done: Classification
+2016-08-24 17:14:15,864 DEBUG: Start: Statistic Results
+2016-08-24 17:14:15,865 DEBUG: Info: Classification report:
+2016-08-24 17:14:15,865 DEBUG:
+ precision recall f1-score support
+
+ Non 0.84 0.88 0.86 24
+ Oui 0.70 0.64 0.67 11
+
+avg / total 0.80 0.80 0.80 35
+
+2016-08-24 17:14:15,876 DEBUG: Info: Statistics:
+2016-08-24 17:14:15,883 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.761905
+5 Mean of F1-Score of top 20 classes by F1-Score 0.761905
+6 Mean of F1-Score of top 30 classes by F1-Score 0.761905
+2016-08-24 17:14:15,883 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:16,173 DEBUG: Done: Statistic Results
+2016-08-24 17:14:16,173 DEBUG: Start: Plot Result
+2016-08-24 17:14:16,378 DEBUG: Done: Plot Result
+2016-08-24 17:14:16,379 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:16,379 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 17:14:16,379 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:16,380 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:16,380 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:16,380 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:16,380 DEBUG: Start: Classification
+2016-08-24 17:14:16,590 DEBUG: Info: Time for Classification: 0.207895994186[s]
+2016-08-24 17:14:16,590 DEBUG: Done: Classification
+2016-08-24 17:14:16,592 DEBUG: Start: Statistic Results
+2016-08-24 17:14:16,592 DEBUG: Info: Classification report:
+2016-08-24 17:14:16,593 DEBUG:
+ precision recall f1-score support
+
+ Non 0.85 0.92 0.88 25
+ Oui 0.75 0.60 0.67 10
+
+avg / total 0.82 0.83 0.82 35
+
+2016-08-24 17:14:16,594 DEBUG: Info: Statistics:
+2016-08-24 17:14:16,601 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.828571428571
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.775641
+5 Mean of F1-Score of top 20 classes by F1-Score 0.775641
+6 Mean of F1-Score of top 30 classes by F1-Score 0.775641
+2016-08-24 17:14:16,602 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:16,883 DEBUG: Done: Statistic Results
+2016-08-24 17:14:16,884 DEBUG: Start: Plot Result
+2016-08-24 17:14:17,095 DEBUG: Done: Plot Result
+2016-08-24 17:14:17,097 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:17,097 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 17:14:17,097 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:17,097 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:17,097 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:17,098 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:17,098 DEBUG: Start: Classification
+2016-08-24 17:14:17,430 DEBUG: Info: Time for Classification: 0.33030295372[s]
+2016-08-24 17:14:17,430 DEBUG: Done: Classification
+2016-08-24 17:14:17,447 DEBUG: Start: Statistic Results
+2016-08-24 17:14:17,447 DEBUG: Info: Classification report:
+2016-08-24 17:14:17,448 DEBUG:
+ precision recall f1-score support
+
+ Non 0.83 0.93 0.88 27
+ Oui 0.60 0.38 0.46 8
+
+avg / total 0.78 0.80 0.78 35
+
+2016-08-24 17:14:17,450 DEBUG: Info: Statistics:
+2016-08-24 17:14:17,457 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.669366
+5 Mean of F1-Score of top 20 classes by F1-Score 0.669366
+6 Mean of F1-Score of top 30 classes by F1-Score 0.669366
+2016-08-24 17:14:17,457 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:17,736 DEBUG: Done: Statistic Results
+2016-08-24 17:14:17,736 DEBUG: Start: Plot Result
+2016-08-24 17:14:17,957 DEBUG: Done: Plot Result
+2016-08-24 17:14:17,958 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:17,958 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 17:14:17,958 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:17,959 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:17,959 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:17,959 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:17,959 DEBUG: Start: Classification
+2016-08-24 17:14:20,605 DEBUG: Info: Time for Classification: 2.64367699623[s]
+2016-08-24 17:14:20,605 DEBUG: Done: Classification
+2016-08-24 17:14:20,613 DEBUG: Start: Statistic Results
+2016-08-24 17:14:20,613 DEBUG: Info: Classification report:
+2016-08-24 17:14:20,614 DEBUG:
+ precision recall f1-score support
+
+ Non 0.93 0.96 0.94 26
+ Oui 0.88 0.78 0.82 9
+
+avg / total 0.91 0.91 0.91 35
+
+2016-08-24 17:14:20,616 DEBUG: Info: Statistics:
+2016-08-24 17:14:20,623 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.914285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.883463
+5 Mean of F1-Score of top 20 classes by F1-Score 0.883463
+6 Mean of F1-Score of top 30 classes by F1-Score 0.883463
+2016-08-24 17:14:20,623 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:20,917 DEBUG: Done: Statistic Results
+2016-08-24 17:14:20,917 DEBUG: Start: Plot Result
+2016-08-24 17:14:21,129 DEBUG: Done: Plot Result
+2016-08-24 17:14:21,130 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:21,130 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SGD
+2016-08-24 17:14:21,131 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:21,131 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:21,131 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:21,131 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:21,131 DEBUG: Start: Classification
+2016-08-24 17:14:21,217 DEBUG: Info: Time for Classification: 0.082671880722[s]
+2016-08-24 17:14:21,217 DEBUG: Done: Classification
+2016-08-24 17:14:21,218 DEBUG: Start: Statistic Results
+2016-08-24 17:14:21,219 DEBUG: Info: Classification report:
+2016-08-24 17:14:21,219 DEBUG:
+ precision recall f1-score support
+
+ Non 0.73 0.90 0.81 21
+ Oui 0.78 0.50 0.61 14
+
+avg / total 0.75 0.74 0.73 35
+
+2016-08-24 17:14:21,222 DEBUG: Info: Statistics:
+2016-08-24 17:14:21,229 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.742857142857
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.708603
+5 Mean of F1-Score of top 20 classes by F1-Score 0.708603
+6 Mean of F1-Score of top 30 classes by F1-Score 0.708603
+2016-08-24 17:14:21,229 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:21,554 DEBUG: Done: Statistic Results
+2016-08-24 17:14:21,554 DEBUG: Start: Plot Result
+2016-08-24 17:14:21,788 DEBUG: Done: Plot Result
+2016-08-24 17:14:21,790 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:21,790 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMLinear
+2016-08-24 17:14:21,790 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:21,790 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:21,790 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:21,791 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:21,791 DEBUG: Start: Classification
+2016-08-24 17:14:33,705 DEBUG: Info: Time for Classification: 11.9117758274[s]
+2016-08-24 17:14:33,705 DEBUG: Done: Classification
+2016-08-24 17:14:33,709 DEBUG: Start: Statistic Results
+2016-08-24 17:14:33,709 DEBUG: Info: Classification report:
+2016-08-24 17:14:33,710 DEBUG:
+ precision recall f1-score support
+
+ Non 0.86 0.90 0.88 21
+ Oui 0.85 0.79 0.81 14
+
+avg / total 0.86 0.86 0.86 35
+
+2016-08-24 17:14:33,712 DEBUG: Info: Statistics:
+2016-08-24 17:14:33,719 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.857142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.849268
+5 Mean of F1-Score of top 20 classes by F1-Score 0.849268
+6 Mean of F1-Score of top 30 classes by F1-Score 0.849268
+2016-08-24 17:14:33,720 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:34,006 DEBUG: Done: Statistic Results
+2016-08-24 17:14:34,006 DEBUG: Start: Plot Result
+2016-08-24 17:14:34,214 DEBUG: Done: Plot Result
+2016-08-24 17:14:34,215 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:34,215 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMPoly
+2016-08-24 17:14:34,216 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:34,216 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:34,216 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:34,216 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:34,216 DEBUG: Start: Classification
+2016-08-24 17:14:50,392 DEBUG: Info: Time for Classification: 16.1731550694[s]
+2016-08-24 17:14:50,392 DEBUG: Done: Classification
+2016-08-24 17:14:50,396 DEBUG: Start: Statistic Results
+2016-08-24 17:14:50,397 DEBUG: Info: Classification report:
+2016-08-24 17:14:50,398 DEBUG:
+ precision recall f1-score support
+
+ Non 0.92 0.83 0.87 29
+ Oui 0.44 0.67 0.53 6
+
+avg / total 0.84 0.80 0.81 35
+
+2016-08-24 17:14:50,400 DEBUG: Info: Statistics:
+2016-08-24 17:14:50,407 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.70303
+5 Mean of F1-Score of top 20 classes by F1-Score 0.70303
+6 Mean of F1-Score of top 30 classes by F1-Score 0.70303
+2016-08-24 17:14:50,407 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:50,693 DEBUG: Done: Statistic Results
+2016-08-24 17:14:50,694 DEBUG: Start: Plot Result
+2016-08-24 17:14:50,901 DEBUG: Done: Plot Result
+2016-08-24 17:14:50,902 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:50,902 DEBUG: ### Classification - Database:MultiOmic Feature:RNASeq train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMRBF
+2016-08-24 17:14:50,902 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:50,903 DEBUG: Info: Shape X_train:(312, 1046), Length of y_train:312
+2016-08-24 17:14:50,903 DEBUG: Info: Shape X_test:(35, 1046), Length of y_test:35
+2016-08-24 17:14:50,903 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:50,903 DEBUG: Start: Classification
+2016-08-24 17:14:51,458 DEBUG: Info: Time for Classification: 0.552815914154[s]
+2016-08-24 17:14:51,458 DEBUG: Done: Classification
+2016-08-24 17:14:51,471 DEBUG: Start: Statistic Results
+2016-08-24 17:14:51,471 DEBUG: Info: Classification report:
+2016-08-24 17:14:51,482 DEBUG:
+ precision recall f1-score support
+
+ Non 0.80 1.00 0.89 28
+ Oui 0.00 0.00 0.00 7
+
+avg / total 0.64 0.80 0.71 35
+
+2016-08-24 17:14:51,484 DEBUG: Info: Statistics:
+2016-08-24 17:14:51,492 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.8
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.444444
+5 Mean of F1-Score of top 20 classes by F1-Score 0.444444
+6 Mean of F1-Score of top 30 classes by F1-Score 0.444444
+2016-08-24 17:14:51,492 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:14:51,798 DEBUG: Done: Statistic Results
+2016-08-24 17:14:51,799 DEBUG: Start: Plot Result
+2016-08-24 17:14:52,015 DEBUG: Done: Plot Result
+2016-08-24 17:14:52,044 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:14:52,044 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:14:52,044 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:14:52,105 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:14:52,105 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:14:52,105 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:14:52,105 DEBUG: Start: Classification
+2016-08-24 17:15:33,379 DEBUG: Info: Time for Classification: 41.3318929672[s]
+2016-08-24 17:15:33,379 DEBUG: Done: Classification
+2016-08-24 17:15:33,384 DEBUG: Start: Statistic Results
+2016-08-24 17:15:33,384 DEBUG: Info: Classification report:
+2016-08-24 17:15:33,385 DEBUG:
+ precision recall f1-score support
+
+ Non 0.67 0.64 0.65 25
+ Oui 0.18 0.20 0.19 10
+
+avg / total 0.53 0.51 0.52 35
+
+2016-08-24 17:15:33,387 DEBUG: Info: Statistics:
+2016-08-24 17:15:33,394 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.514285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.421769
+5 Mean of F1-Score of top 20 classes by F1-Score 0.421769
+6 Mean of F1-Score of top 30 classes by F1-Score 0.421769
+2016-08-24 17:15:33,394 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:15:33,680 DEBUG: Done: Statistic Results
+2016-08-24 17:15:33,680 DEBUG: Start: Plot Result
+2016-08-24 17:15:33,894 DEBUG: Done: Plot Result
+2016-08-24 17:15:33,924 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:15:33,924 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 17:15:33,924 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:15:33,960 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:15:33,960 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:15:33,960 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:15:33,960 DEBUG: Start: Classification
+2016-08-24 17:15:53,507 DEBUG: Info: Time for Classification: 19.5791618824[s]
+2016-08-24 17:15:53,507 DEBUG: Done: Classification
+2016-08-24 17:15:53,510 DEBUG: Start: Statistic Results
+2016-08-24 17:15:53,510 DEBUG: Info: Classification report:
+2016-08-24 17:15:53,511 DEBUG:
+ precision recall f1-score support
+
+ Non 0.80 0.71 0.75 28
+ Oui 0.20 0.29 0.24 7
+
+avg / total 0.68 0.63 0.65 35
+
+2016-08-24 17:15:53,513 DEBUG: Info: Statistics:
+2016-08-24 17:15:53,535 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.628571428571
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.495006
+5 Mean of F1-Score of top 20 classes by F1-Score 0.495006
+6 Mean of F1-Score of top 30 classes by F1-Score 0.495006
+2016-08-24 17:15:53,535 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:15:53,808 DEBUG: Done: Statistic Results
+2016-08-24 17:15:53,809 DEBUG: Start: Plot Result
+2016-08-24 17:15:54,018 DEBUG: Done: Plot Result
+2016-08-24 17:15:54,047 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:15:54,047 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 17:15:54,047 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:15:54,082 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:15:54,082 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:15:54,082 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:15:54,083 DEBUG: Start: Classification
+2016-08-24 17:16:20,926 DEBUG: Info: Time for Classification: 26.8760640621[s]
+2016-08-24 17:16:20,926 DEBUG: Done: Classification
+2016-08-24 17:16:22,296 DEBUG: Start: Statistic Results
+2016-08-24 17:16:22,296 DEBUG: Info: Classification report:
+2016-08-24 17:16:22,297 DEBUG:
+ precision recall f1-score support
+
+ Non 0.74 0.96 0.83 26
+ Oui 0.00 0.00 0.00 9
+
+avg / total 0.55 0.71 0.62 35
+
+2016-08-24 17:16:22,299 DEBUG: Info: Statistics:
+2016-08-24 17:16:22,306 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.416667
+5 Mean of F1-Score of top 20 classes by F1-Score 0.416667
+6 Mean of F1-Score of top 30 classes by F1-Score 0.416667
+2016-08-24 17:16:22,306 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:16:22,613 DEBUG: Done: Statistic Results
+2016-08-24 17:16:22,613 DEBUG: Start: Plot Result
+2016-08-24 17:16:24,168 DEBUG: Done: Plot Result
+2016-08-24 17:16:24,275 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:16:24,275 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 17:16:24,275 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:16:24,311 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:16:24,311 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:16:24,311 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:16:24,311 DEBUG: Start: Classification
+2016-08-24 17:16:35,981 DEBUG: Info: Time for Classification: 11.7026500702[s]
+2016-08-24 17:16:35,981 DEBUG: Done: Classification
+2016-08-24 17:16:35,991 DEBUG: Start: Statistic Results
+2016-08-24 17:16:35,991 DEBUG: Info: Classification report:
+2016-08-24 17:16:35,992 DEBUG:
+ precision recall f1-score support
+
+ Non 0.71 1.00 0.83 24
+ Oui 1.00 0.09 0.17 11
+
+avg / total 0.80 0.71 0.62 35
+
+2016-08-24 17:16:35,994 DEBUG: Info: Statistics:
+2016-08-24 17:16:36,001 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.497126
+5 Mean of F1-Score of top 20 classes by F1-Score 0.497126
+6 Mean of F1-Score of top 30 classes by F1-Score 0.497126
+2016-08-24 17:16:36,001 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:16:36,287 DEBUG: Done: Statistic Results
+2016-08-24 17:16:36,287 DEBUG: Start: Plot Result
+2016-08-24 17:16:36,501 DEBUG: Done: Plot Result
+2016-08-24 17:16:36,530 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:16:36,530 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SGD
+2016-08-24 17:16:36,530 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:16:36,566 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:16:36,566 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:16:36,566 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:16:36,566 DEBUG: Start: Classification
+2016-08-24 17:16:39,126 DEBUG: Info: Time for Classification: 2.59249281883[s]
+2016-08-24 17:16:39,126 DEBUG: Done: Classification
+2016-08-24 17:16:39,135 DEBUG: Start: Statistic Results
+2016-08-24 17:16:39,135 DEBUG: Info: Classification report:
+2016-08-24 17:16:39,136 DEBUG:
+ precision recall f1-score support
+
+ Non 0.67 0.75 0.71 24
+ Oui 0.25 0.18 0.21 11
+
+avg / total 0.54 0.57 0.55 35
+
+2016-08-24 17:16:39,138 DEBUG: Info: Statistics:
+2016-08-24 17:16:39,146 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.571428571429
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.458204
+5 Mean of F1-Score of top 20 classes by F1-Score 0.458204
+6 Mean of F1-Score of top 30 classes by F1-Score 0.458204
+2016-08-24 17:16:39,146 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:16:39,466 DEBUG: Done: Statistic Results
+2016-08-24 17:16:39,466 DEBUG: Start: Plot Result
+2016-08-24 17:16:39,708 DEBUG: Done: Plot Result
+2016-08-24 17:16:39,740 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:16:39,740 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMLinear
+2016-08-24 17:16:39,740 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:16:39,780 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:16:39,780 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:16:39,780 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:16:39,780 DEBUG: Start: Classification
+2016-08-24 17:17:12,799 DEBUG: Info: Time for Classification: 33.0559568405[s]
+2016-08-24 17:17:12,800 DEBUG: Done: Classification
+2016-08-24 17:17:13,409 DEBUG: Start: Statistic Results
+2016-08-24 17:17:13,409 DEBUG: Info: Classification report:
+2016-08-24 17:17:13,410 DEBUG:
+ precision recall f1-score support
+
+ Non 0.74 0.68 0.71 25
+ Oui 0.33 0.40 0.36 10
+
+avg / total 0.62 0.60 0.61 35
+
+2016-08-24 17:17:13,412 DEBUG: Info: Statistics:
+2016-08-24 17:17:13,419 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.6
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.535985
+5 Mean of F1-Score of top 20 classes by F1-Score 0.535985
+6 Mean of F1-Score of top 30 classes by F1-Score 0.535985
+2016-08-24 17:17:13,419 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:17:13,707 DEBUG: Done: Statistic Results
+2016-08-24 17:17:13,707 DEBUG: Start: Plot Result
+2016-08-24 17:17:14,521 DEBUG: Done: Plot Result
+2016-08-24 17:17:14,557 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:17:14,557 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMPoly
+2016-08-24 17:17:14,557 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:17:14,593 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:17:14,593 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:17:14,594 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:17:14,594 DEBUG: Start: Classification
+2016-08-24 17:19:04,671 DEBUG: Info: Time for Classification: 110.109973192[s]
+2016-08-24 17:19:04,671 DEBUG: Done: Classification
+2016-08-24 17:19:05,281 DEBUG: Start: Statistic Results
+2016-08-24 17:19:05,281 DEBUG: Info: Classification report:
+2016-08-24 17:19:05,282 DEBUG:
+ precision recall f1-score support
+
+ Non 0.77 0.92 0.84 25
+ Oui 0.60 0.30 0.40 10
+
+avg / total 0.72 0.74 0.71 35
+
+2016-08-24 17:19:05,284 DEBUG: Info: Statistics:
+2016-08-24 17:19:05,291 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.742857142857
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.618182
+5 Mean of F1-Score of top 20 classes by F1-Score 0.618182
+6 Mean of F1-Score of top 30 classes by F1-Score 0.618182
+2016-08-24 17:19:05,291 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:19:05,584 DEBUG: Done: Statistic Results
+2016-08-24 17:19:05,584 DEBUG: Start: Plot Result
+2016-08-24 17:19:06,399 DEBUG: Done: Plot Result
+2016-08-24 17:19:06,435 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:19:06,435 DEBUG: ### Classification - Database:MultiOmic Feature:Clinic train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMRBF
+2016-08-24 17:19:06,435 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:19:06,471 DEBUG: Info: Shape X_train:(312, 73599), Length of y_train:312
+2016-08-24 17:19:06,471 DEBUG: Info: Shape X_test:(35, 73599), Length of y_test:35
+2016-08-24 17:19:06,471 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:19:06,471 DEBUG: Start: Classification
+2016-08-24 17:19:44,657 DEBUG: Info: Time for Classification: 38.2183771133[s]
+2016-08-24 17:19:44,657 DEBUG: Done: Classification
+2016-08-24 17:19:45,518 DEBUG: Start: Statistic Results
+2016-08-24 17:19:45,518 DEBUG: Info: Classification report:
+2016-08-24 17:19:45,519 DEBUG:
+ precision recall f1-score support
+
+ Non 0.77 1.00 0.87 27
+ Oui 0.00 0.00 0.00 8
+
+avg / total 0.60 0.77 0.67 35
+
+2016-08-24 17:19:45,521 DEBUG: Info: Statistics:
+2016-08-24 17:19:45,528 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.771428571429
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.435484
+5 Mean of F1-Score of top 20 classes by F1-Score 0.435484
+6 Mean of F1-Score of top 30 classes by F1-Score 0.435484
+2016-08-24 17:19:45,528 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:19:45,835 DEBUG: Done: Statistic Results
+2016-08-24 17:19:45,835 DEBUG: Start: Plot Result
+2016-08-24 17:19:46,893 DEBUG: Done: Plot Result
+2016-08-24 17:19:46,931 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:19:46,931 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : Adaboost
+2016-08-24 17:19:46,931 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:19:46,931 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:19:46,932 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:19:46,932 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:19:46,932 DEBUG: Start: Classification
+2016-08-24 17:19:47,048 DEBUG: Info: Time for Classification: 0.114088058472[s]
+2016-08-24 17:19:47,048 DEBUG: Done: Classification
+2016-08-24 17:19:47,050 DEBUG: Start: Statistic Results
+2016-08-24 17:19:47,050 DEBUG: Info: Classification report:
+2016-08-24 17:19:47,051 DEBUG:
+ precision recall f1-score support
+
+ Non 0.91 1.00 0.95 21
+ Oui 1.00 0.86 0.92 14
+
+avg / total 0.95 0.94 0.94 35
+
+2016-08-24 17:19:47,053 DEBUG: Info: Statistics:
+2016-08-24 17:19:47,060 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.942857142857
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.938811
+5 Mean of F1-Score of top 20 classes by F1-Score 0.938811
+6 Mean of F1-Score of top 30 classes by F1-Score 0.938811
+2016-08-24 17:19:47,060 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:19:47,348 DEBUG: Done: Statistic Results
+2016-08-24 17:19:47,349 DEBUG: Start: Plot Result
+2016-08-24 17:19:47,573 DEBUG: Done: Plot Result
+2016-08-24 17:19:47,574 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:19:47,574 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : DecisionTree
+2016-08-24 17:19:47,575 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:19:47,575 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:19:47,575 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:19:47,575 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:19:47,575 DEBUG: Start: Classification
+2016-08-24 17:19:47,616 DEBUG: Info: Time for Classification: 0.038232088089[s]
+2016-08-24 17:19:47,616 DEBUG: Done: Classification
+2016-08-24 17:19:47,617 DEBUG: Start: Statistic Results
+2016-08-24 17:19:47,618 DEBUG: Info: Classification report:
+2016-08-24 17:19:47,618 DEBUG:
+ precision recall f1-score support
+
+ Non 0.71 1.00 0.83 25
+ Oui 0.00 0.00 0.00 10
+
+avg / total 0.51 0.71 0.60 35
+
+2016-08-24 17:19:47,620 DEBUG: Info: Statistics:
+2016-08-24 17:19:47,637 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.416667
+5 Mean of F1-Score of top 20 classes by F1-Score 0.416667
+6 Mean of F1-Score of top 30 classes by F1-Score 0.416667
+2016-08-24 17:19:47,637 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:19:47,922 DEBUG: Done: Statistic Results
+2016-08-24 17:19:47,922 DEBUG: Start: Plot Result
+2016-08-24 17:19:48,128 DEBUG: Done: Plot Result
+2016-08-24 17:19:48,129 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:19:48,129 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : KNN
+2016-08-24 17:19:48,129 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:19:48,129 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:19:48,130 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:19:48,130 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:19:48,130 DEBUG: Start: Classification
+2016-08-24 17:19:48,211 DEBUG: Info: Time for Classification: 0.0789890289307[s]
+2016-08-24 17:19:48,211 DEBUG: Done: Classification
+2016-08-24 17:19:48,214 DEBUG: Start: Statistic Results
+2016-08-24 17:19:48,215 DEBUG: Info: Classification report:
+2016-08-24 17:19:48,215 DEBUG:
+ precision recall f1-score support
+
+ Non 0.69 1.00 0.81 24
+ Oui 0.00 0.00 0.00 11
+
+avg / total 0.47 0.69 0.56 35
+
+2016-08-24 17:19:48,217 DEBUG: Info: Statistics:
+2016-08-24 17:19:48,224 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.685714285714
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.40678
+5 Mean of F1-Score of top 20 classes by F1-Score 0.40678
+6 Mean of F1-Score of top 30 classes by F1-Score 0.40678
+2016-08-24 17:19:48,225 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:19:48,505 DEBUG: Done: Statistic Results
+2016-08-24 17:19:48,505 DEBUG: Start: Plot Result
+2016-08-24 17:19:48,713 DEBUG: Done: Plot Result
+2016-08-24 17:19:48,714 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:19:48,714 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : RandomForest
+2016-08-24 17:19:48,714 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:19:48,714 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:19:48,715 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:19:48,715 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:19:48,715 DEBUG: Start: Classification
+2016-08-24 17:19:51,055 DEBUG: Info: Time for Classification: 2.3381061554[s]
+2016-08-24 17:19:51,055 DEBUG: Done: Classification
+2016-08-24 17:19:51,067 DEBUG: Start: Statistic Results
+2016-08-24 17:19:51,068 DEBUG: Info: Classification report:
+2016-08-24 17:19:51,069 DEBUG:
+ precision recall f1-score support
+
+ Non 0.88 1.00 0.93 28
+ Oui 1.00 0.43 0.60 7
+
+avg / total 0.90 0.89 0.87 35
+
+2016-08-24 17:19:51,070 DEBUG: Info: Statistics:
+2016-08-24 17:19:51,077 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.885714285714
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.766667
+5 Mean of F1-Score of top 20 classes by F1-Score 0.766667
+6 Mean of F1-Score of top 30 classes by F1-Score 0.766667
+2016-08-24 17:19:51,077 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:19:51,369 DEBUG: Done: Statistic Results
+2016-08-24 17:19:51,370 DEBUG: Start: Plot Result
+2016-08-24 17:19:51,587 DEBUG: Done: Plot Result
+2016-08-24 17:19:51,589 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:19:51,589 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SGD
+2016-08-24 17:19:51,589 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:19:51,589 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:19:51,589 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:19:51,589 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:19:51,589 DEBUG: Start: Classification
+2016-08-24 17:19:51,655 DEBUG: Info: Time for Classification: 0.0632700920105[s]
+2016-08-24 17:19:51,656 DEBUG: Done: Classification
+2016-08-24 17:19:51,657 DEBUG: Start: Statistic Results
+2016-08-24 17:19:51,657 DEBUG: Info: Classification report:
+2016-08-24 17:19:51,658 DEBUG:
+ precision recall f1-score support
+
+ Non 1.00 0.14 0.25 28
+ Oui 0.23 1.00 0.37 7
+
+avg / total 0.85 0.31 0.27 35
+
+2016-08-24 17:19:51,660 DEBUG: Info: Statistics:
+2016-08-24 17:19:51,668 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.314285714286
+1 Top 10 classes by F1-Score [Oui, Non]
+2 Worst 10 classes by F1-Score [Non, Oui]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.309211
+5 Mean of F1-Score of top 20 classes by F1-Score 0.309211
+6 Mean of F1-Score of top 30 classes by F1-Score 0.309211
+2016-08-24 17:19:51,668 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:19:51,992 DEBUG: Done: Statistic Results
+2016-08-24 17:19:51,993 DEBUG: Start: Plot Result
+2016-08-24 17:19:52,241 DEBUG: Done: Plot Result
+2016-08-24 17:19:52,242 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:19:52,242 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMLinear
+2016-08-24 17:19:52,242 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:19:52,242 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:19:52,242 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:19:52,242 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:19:52,242 DEBUG: Start: Classification
+2016-08-24 17:21:47,120 DEBUG: Info: Time for Classification: 114.874765158[s]
+2016-08-24 17:21:47,120 DEBUG: Done: Classification
+2016-08-24 17:21:47,122 DEBUG: Start: Statistic Results
+2016-08-24 17:21:47,122 DEBUG: Info: Classification report:
+2016-08-24 17:21:47,123 DEBUG:
+ precision recall f1-score support
+
+ Non 0.93 0.87 0.90 30
+ Oui 0.43 0.60 0.50 5
+
+avg / total 0.86 0.83 0.84 35
+
+2016-08-24 17:21:47,125 DEBUG: Info: Statistics:
+2016-08-24 17:21:47,132 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.828571428571
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.698276
+5 Mean of F1-Score of top 20 classes by F1-Score 0.698276
+6 Mean of F1-Score of top 30 classes by F1-Score 0.698276
+2016-08-24 17:21:47,132 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:21:47,411 DEBUG: Done: Statistic Results
+2016-08-24 17:21:47,411 DEBUG: Start: Plot Result
+2016-08-24 17:21:47,619 DEBUG: Done: Plot Result
+2016-08-24 17:21:47,620 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:21:47,620 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMPoly
+2016-08-24 17:21:47,620 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:21:47,620 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:21:47,620 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:21:47,620 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:21:47,621 DEBUG: Start: Classification
+2016-08-24 17:26:12,253 DEBUG: Info: Time for Classification: 264.629760981[s]
+2016-08-24 17:26:12,253 DEBUG: Done: Classification
+2016-08-24 17:26:12,255 DEBUG: Start: Statistic Results
+2016-08-24 17:26:12,255 DEBUG: Info: Classification report:
+2016-08-24 17:26:12,256 DEBUG:
+ precision recall f1-score support
+
+ Non 0.81 0.81 0.81 27
+ Oui 0.38 0.38 0.38 8
+
+avg / total 0.71 0.71 0.71 35
+
+2016-08-24 17:26:12,258 DEBUG: Info: Statistics:
+2016-08-24 17:26:12,265 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.714285714286
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0
+4 Mean of F1-Score of top 10 classes by F1-Score 0.594907
+5 Mean of F1-Score of top 20 classes by F1-Score 0.594907
+6 Mean of F1-Score of top 30 classes by F1-Score 0.594907
+2016-08-24 17:26:12,266 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:26:12,563 DEBUG: Done: Statistic Results
+2016-08-24 17:26:12,564 DEBUG: Start: Plot Result
+2016-08-24 17:26:12,784 DEBUG: Done: Plot Result
+2016-08-24 17:26:12,785 DEBUG: ### Main Programm for Classification MonoView
+2016-08-24 17:26:12,785 DEBUG: ### Classification - Database:MultiOmic Feature:Methyl train_size:0.9, CrossValidation k-folds:2, cores:1, algorithm : SVMRBF
+2016-08-24 17:26:12,785 DEBUG: Start: Determine Train/Test split
+2016-08-24 17:26:12,786 DEBUG: Info: Shape X_train:(312, 127), Length of y_train:312
+2016-08-24 17:26:12,786 DEBUG: Info: Shape X_test:(35, 127), Length of y_test:35
+2016-08-24 17:26:12,786 DEBUG: Done: Determine Train/Test split
+2016-08-24 17:26:12,786 DEBUG: Start: Classification
+2016-08-24 17:26:12,940 DEBUG: Info: Time for Classification: 0.151942014694[s]
+2016-08-24 17:26:12,941 DEBUG: Done: Classification
+2016-08-24 17:26:12,944 DEBUG: Start: Statistic Results
+2016-08-24 17:26:12,944 DEBUG: Info: Classification report:
+2016-08-24 17:26:12,945 DEBUG:
+ precision recall f1-score support
+
+ Non 0.66 1.00 0.79 23
+ Oui 0.00 0.00 0.00 12
+
+avg / total 0.43 0.66 0.52 35
+
+2016-08-24 17:26:12,947 DEBUG: Info: Statistics:
+2016-08-24 17:26:12,954 DEBUG:
+ Statistic Values
+0 Accuracy score on test 0.657142857143
+1 Top 10 classes by F1-Score [Non, Oui]
+2 Worst 10 classes by F1-Score [Oui, Non]
+3 Ratio of classes with F1-Score==0 of all classes 0.5
+4 Mean of F1-Score of top 10 classes by F1-Score 0.396552
+5 Mean of F1-Score of top 20 classes by F1-Score 0.396552
+6 Mean of F1-Score of top 30 classes by F1-Score 0.396552
+2016-08-24 17:26:12,954 DEBUG: Info: Calculate Confusionmatrix
+2016-08-24 17:26:13,253 DEBUG: Done: Statistic Results
+2016-08-24 17:26:13,253 DEBUG: Start: Plot Result
+2016-08-24 17:26:13,526 DEBUG: Done: Plot Result
+2016-08-24 17:26:13,630 INFO: ### Main Programm for Multiview Classification
+2016-08-24 17:26:13,630 INFO: ### Classification - Database : MultiOmic ; Views : Methyl, MiRNA_, RNASeq, Clinic ; Algorithm : Mumbo ; Cores : 1
+2016-08-24 17:26:13,631 INFO: Info: Shape of Methyl :(347, 25978)
+2016-08-24 17:26:13,631 INFO: Info: Shape of MiRNA_ :(347, 1046)
+2016-08-24 17:26:13,632 INFO: Info: Shape of RANSeq :(347, 73599)
+2016-08-24 17:26:13,632 INFO: Info: Shape of Clinic :(347, 127)
+2016-08-24 17:26:13,632 INFO: Done: Read Database Files
+2016-08-24 17:26:13,632 INFO: Start: Determine validation split for ratio 0.9
+2016-08-24 17:26:13,635 INFO: Done: Determine validation split
+2016-08-24 17:26:13,635 INFO: Start: Determine 2 folds
+2016-08-24 17:26:13,649 INFO: Info: Length of Learning Sets: 157
+2016-08-24 17:26:13,649 INFO: Info: Length of Testing Sets: 156
+2016-08-24 17:26:13,650 INFO: Info: Length of Validation Set: 34
+2016-08-24 17:26:13,650 INFO: Done: Determine folds
+2016-08-24 17:26:13,650 INFO: Start: Learning with Mumbo and 2 folds
+2016-08-24 17:26:13,650 INFO: Start: Gridsearching best settings for monoview classifiers
+2016-08-24 17:26:13,650 DEBUG: Start: Gridsearch for DecisionTree on Methyl
+2016-08-24 17:26:21,801 DEBUG: Info: Best Reslut : 0.516253602305
+2016-08-24 17:26:21,801 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:26:21,801 DEBUG: Start: Gridsearch for DecisionTree on MiRNA_
+2016-08-24 17:26:23,966 DEBUG: Info: Best Reslut : 0.565129682997
+2016-08-24 17:26:23,967 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:26:23,967 DEBUG: Start: Gridsearch for DecisionTree on RANSeq
+2016-08-24 17:26:42,003 DEBUG: Info: Best Reslut : 0.51204610951
+2016-08-24 17:26:42,004 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:26:42,004 DEBUG: Start: Gridsearch for DecisionTree on Clinic
+2016-08-24 17:26:43,930 DEBUG: Info: Best Reslut : 0.514236311239
+2016-08-24 17:26:43,931 DEBUG: Done: Gridsearch for DecisionTree
+2016-08-24 17:26:43,931 INFO: Done: Gridsearching best settings for monoview classifiers
+2016-08-24 17:26:43,931 INFO: Start: Fold number 1
+2016-08-24 17:26:45,766 DEBUG: Start: Iteration 1
+2016-08-24 17:26:45,796 DEBUG: View 0 : 0.706896551724
+2016-08-24 17:26:45,805 DEBUG: View 1 : 0.706896551724
+2016-08-24 17:26:45,836 DEBUG: View 2 : 0.706896551724
+2016-08-24 17:26:45,845 DEBUG: View 3 : 0.706896551724
+2016-08-24 17:26:45,892 DEBUG: Best view : Methyl
+2016-08-24 17:26:45,977 DEBUG: Start: Iteration 2
+2016-08-24 17:26:45,995 DEBUG: View 0 : 0.551724137931
+2016-08-24 17:26:46,004 DEBUG: View 1 : 0.442528735632
+2016-08-24 17:26:46,043 DEBUG: View 2 : 0.683908045977
+2016-08-24 17:26:46,052 DEBUG: View 3 : 0.614942528736
+2016-08-24 17:26:46,105 DEBUG: Best view : RANSeq
+2016-08-24 17:26:46,271 DEBUG: Start: Iteration 3
+2016-08-24 17:26:46,289 DEBUG: View 0 : 0.431034482759
+2016-08-24 17:26:46,297 DEBUG: View 1 : 0.310344827586
+2016-08-24 17:26:46,337 DEBUG: View 2 : 0.522988505747
+2016-08-24 17:26:46,345 DEBUG: View 3 : 0.695402298851
+2016-08-24 17:26:46,406 DEBUG: Best view : Clinic
+2016-08-24 17:26:46,638 DEBUG: Start: Iteration 4
+2016-08-24 17:26:46,656 DEBUG: View 0 : 0.465517241379
+2016-08-24 17:26:46,666 DEBUG: View 1 : 0.729885057471
+2016-08-24 17:26:46,706 DEBUG: View 2 : 0.522988505747
+2016-08-24 17:26:46,715 DEBUG: View 3 : 0.471264367816
+2016-08-24 17:26:46,780 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:47,078 DEBUG: Start: Iteration 5
+2016-08-24 17:26:47,099 DEBUG: View 0 : 0.557471264368
+2016-08-24 17:26:47,108 DEBUG: View 1 : 0.729885057471
+2016-08-24 17:26:47,148 DEBUG: View 2 : 0.465517241379
+2016-08-24 17:26:47,156 DEBUG: View 3 : 0.442528735632
+2016-08-24 17:26:47,222 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:47,581 DEBUG: Start: Iteration 6
+2016-08-24 17:26:47,599 DEBUG: View 0 : 0.580459770115
+2016-08-24 17:26:47,607 DEBUG: View 1 : 0.718390804598
+2016-08-24 17:26:47,647 DEBUG: View 2 : 0.436781609195
+2016-08-24 17:26:47,655 DEBUG: View 3 : 0.350574712644
+2016-08-24 17:26:47,724 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:48,163 DEBUG: Start: Iteration 7
+2016-08-24 17:26:48,181 DEBUG: View 0 : 0.367816091954
+2016-08-24 17:26:48,191 DEBUG: View 1 : 0.614942528736
+2016-08-24 17:26:48,230 DEBUG: View 2 : 0.66091954023
+2016-08-24 17:26:48,239 DEBUG: View 3 : 0.413793103448
+2016-08-24 17:26:48,310 DEBUG: Best view : RANSeq
+2016-08-24 17:26:48,811 DEBUG: Start: Iteration 8
+2016-08-24 17:26:48,829 DEBUG: View 0 : 0.488505747126
+2016-08-24 17:26:48,838 DEBUG: View 1 : 0.706896551724
+2016-08-24 17:26:48,878 DEBUG: View 2 : 0.591954022989
+2016-08-24 17:26:48,887 DEBUG: View 3 : 0.522988505747
+2016-08-24 17:26:48,961 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:49,526 DEBUG: Start: Iteration 9
+2016-08-24 17:26:49,545 DEBUG: View 0 : 0.413793103448
+2016-08-24 17:26:49,554 DEBUG: View 1 : 0.436781609195
+2016-08-24 17:26:49,593 DEBUG: View 2 : 0.522988505747
+2016-08-24 17:26:49,602 DEBUG: View 3 : 0.614942528736
+2016-08-24 17:26:49,681 DEBUG: Best view : Clinic
+2016-08-24 17:26:50,309 DEBUG: Start: Iteration 10
+2016-08-24 17:26:50,327 DEBUG: View 0 : 0.637931034483
+2016-08-24 17:26:50,336 DEBUG: View 1 : 0.494252873563
+2016-08-24 17:26:50,376 DEBUG: View 2 : 0.488505747126
+2016-08-24 17:26:50,384 DEBUG: View 3 : 0.66091954023
+2016-08-24 17:26:50,465 DEBUG: Best view : Clinic
+2016-08-24 17:26:51,156 DEBUG: Start: Iteration 11
+2016-08-24 17:26:51,174 DEBUG: View 0 : 0.689655172414
+2016-08-24 17:26:51,184 DEBUG: View 1 : 0.655172413793
+2016-08-24 17:26:51,223 DEBUG: View 2 : 0.701149425287
+2016-08-24 17:26:51,232 DEBUG: View 3 : 0.488505747126
+2016-08-24 17:26:51,316 DEBUG: Best view : Methyl
+2016-08-24 17:26:52,083 DEBUG: Start: Iteration 12
+2016-08-24 17:26:52,101 DEBUG: View 0 : 0.540229885057
+2016-08-24 17:26:52,110 DEBUG: View 1 : 0.591954022989
+2016-08-24 17:26:52,149 DEBUG: View 2 : 0.367816091954
+2016-08-24 17:26:52,158 DEBUG: View 3 : 0.48275862069
+2016-08-24 17:26:52,244 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:53,068 DEBUG: Start: Iteration 13
+2016-08-24 17:26:53,087 DEBUG: View 0 : 0.459770114943
+2016-08-24 17:26:53,095 DEBUG: View 1 : 0.591954022989
+2016-08-24 17:26:53,135 DEBUG: View 2 : 0.350574712644
+2016-08-24 17:26:53,144 DEBUG: View 3 : 0.350574712644
+2016-08-24 17:26:53,234 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:54,133 DEBUG: Start: Iteration 14
+2016-08-24 17:26:54,152 DEBUG: View 0 : 0.362068965517
+2016-08-24 17:26:54,162 DEBUG: View 1 : 0.51724137931
+2016-08-24 17:26:54,202 DEBUG: View 2 : 0.695402298851
+2016-08-24 17:26:54,211 DEBUG: View 3 : 0.304597701149
+2016-08-24 17:26:54,305 DEBUG: Best view : RANSeq
+2016-08-24 17:26:55,286 DEBUG: Start: Iteration 15
+2016-08-24 17:26:55,305 DEBUG: View 0 : 0.436781609195
+2016-08-24 17:26:55,314 DEBUG: View 1 : 0.494252873563
+2016-08-24 17:26:55,354 DEBUG: View 2 : 0.459770114943
+2016-08-24 17:26:55,362 DEBUG: View 3 : 0.367816091954
+2016-08-24 17:26:55,363 WARNING: WARNING: All bad for iteration 14
+2016-08-24 17:26:55,458 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:56,490 DEBUG: Start: Iteration 16
+2016-08-24 17:26:56,509 DEBUG: View 0 : 0.396551724138
+2016-08-24 17:26:56,518 DEBUG: View 1 : 0.735632183908
+2016-08-24 17:26:56,562 DEBUG: View 2 : 0.706896551724
+2016-08-24 17:26:56,571 DEBUG: View 3 : 0.522988505747
+2016-08-24 17:26:56,670 DEBUG: Best view : MiRNA_
+2016-08-24 17:26:57,816 DEBUG: Start: Iteration 17
+2016-08-24 17:26:57,836 DEBUG: View 0 : 0.649425287356
+2016-08-24 17:26:57,846 DEBUG: View 1 : 0.465517241379
+2016-08-24 17:26:57,901 DEBUG: View 2 : 0.649425287356
+2016-08-24 17:26:57,915 DEBUG: View 3 : 0.672413793103
+2016-08-24 17:26:58,024 DEBUG: Best view : Methyl
+2016-08-24 17:26:59,247 DEBUG: Start: Iteration 18
+2016-08-24 17:26:59,266 DEBUG: View 0 : 0.551724137931
+2016-08-24 17:26:59,275 DEBUG: View 1 : 0.712643678161
+2016-08-24 17:26:59,315 DEBUG: View 2 : 0.551724137931
+2016-08-24 17:26:59,324 DEBUG: View 3 : 0.620689655172
+2016-08-24 17:26:59,430 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:00,676 DEBUG: Start: Iteration 19
+2016-08-24 17:27:00,696 DEBUG: View 0 : 0.689655172414
+2016-08-24 17:27:00,706 DEBUG: View 1 : 0.701149425287
+2016-08-24 17:27:00,748 DEBUG: View 2 : 0.655172413793
+2016-08-24 17:27:00,756 DEBUG: View 3 : 0.419540229885
+2016-08-24 17:27:00,869 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:02,190 DEBUG: Start: Iteration 20
+2016-08-24 17:27:02,209 DEBUG: View 0 : 0.477011494253
+2016-08-24 17:27:02,219 DEBUG: View 1 : 0.67816091954
+2016-08-24 17:27:02,262 DEBUG: View 2 : 0.649425287356
+2016-08-24 17:27:02,271 DEBUG: View 3 : 0.333333333333
+2016-08-24 17:27:02,388 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:03,782 DEBUG: Start: Iteration 21
+2016-08-24 17:27:03,800 DEBUG: View 0 : 0.67816091954
+2016-08-24 17:27:03,809 DEBUG: View 1 : 0.511494252874
+2016-08-24 17:27:03,848 DEBUG: View 2 : 0.48275862069
+2016-08-24 17:27:03,857 DEBUG: View 3 : 0.655172413793
+2016-08-24 17:27:03,969 DEBUG: Best view : Methyl
+2016-08-24 17:27:05,395 DEBUG: Start: Iteration 22
+2016-08-24 17:27:05,414 DEBUG: View 0 : 0.672413793103
+2016-08-24 17:27:05,423 DEBUG: View 1 : 0.465517241379
+2016-08-24 17:27:05,463 DEBUG: View 2 : 0.327586206897
+2016-08-24 17:27:05,471 DEBUG: View 3 : 0.459770114943
+2016-08-24 17:27:05,588 DEBUG: Best view : Methyl
+2016-08-24 17:27:07,113 DEBUG: Start: Iteration 23
+2016-08-24 17:27:07,131 DEBUG: View 0 : 0.344827586207
+2016-08-24 17:27:07,140 DEBUG: View 1 : 0.666666666667
+2016-08-24 17:27:07,179 DEBUG: View 2 : 0.655172413793
+2016-08-24 17:27:07,188 DEBUG: View 3 : 0.672413793103
+2016-08-24 17:27:07,305 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:08,889 DEBUG: Start: Iteration 24
+2016-08-24 17:27:08,907 DEBUG: View 0 : 0.66091954023
+2016-08-24 17:27:08,916 DEBUG: View 1 : 0.275862068966
+2016-08-24 17:27:08,956 DEBUG: View 2 : 0.471264367816
+2016-08-24 17:27:08,965 DEBUG: View 3 : 0.465517241379
+2016-08-24 17:27:09,088 DEBUG: Best view : Methyl
+2016-08-24 17:27:10,750 DEBUG: Start: Iteration 25
+2016-08-24 17:27:10,769 DEBUG: View 0 : 0.33908045977
+2016-08-24 17:27:10,778 DEBUG: View 1 : 0.545977011494
+2016-08-24 17:27:10,819 DEBUG: View 2 : 0.568965517241
+2016-08-24 17:27:10,827 DEBUG: View 3 : 0.33908045977
+2016-08-24 17:27:10,955 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:12,704 DEBUG: Start: Iteration 26
+2016-08-24 17:27:12,724 DEBUG: View 0 : 0.540229885057
+2016-08-24 17:27:12,733 DEBUG: View 1 : 0.724137931034
+2016-08-24 17:27:12,775 DEBUG: View 2 : 0.557471264368
+2016-08-24 17:27:12,784 DEBUG: View 3 : 0.586206896552
+2016-08-24 17:27:12,910 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:14,655 DEBUG: Start: Iteration 27
+2016-08-24 17:27:14,674 DEBUG: View 0 : 0.67816091954
+2016-08-24 17:27:14,683 DEBUG: View 1 : 0.626436781609
+2016-08-24 17:27:14,722 DEBUG: View 2 : 0.580459770115
+2016-08-24 17:27:14,730 DEBUG: View 3 : 0.408045977011
+2016-08-24 17:27:14,859 DEBUG: Best view : Methyl
+2016-08-24 17:27:16,745 DEBUG: Start: Iteration 28
+2016-08-24 17:27:16,764 DEBUG: View 0 : 0.442528735632
+2016-08-24 17:27:16,773 DEBUG: View 1 : 0.494252873563
+2016-08-24 17:27:16,813 DEBUG: View 2 : 0.666666666667
+2016-08-24 17:27:16,822 DEBUG: View 3 : 0.534482758621
+2016-08-24 17:27:16,954 DEBUG: Best view : RANSeq
+2016-08-24 17:27:18,894 DEBUG: Start: Iteration 29
+2016-08-24 17:27:18,912 DEBUG: View 0 : 0.465517241379
+2016-08-24 17:27:18,921 DEBUG: View 1 : 0.408045977011
+2016-08-24 17:27:18,961 DEBUG: View 2 : 0.586206896552
+2016-08-24 17:27:18,969 DEBUG: View 3 : 0.48275862069
+2016-08-24 17:27:19,109 DEBUG: Best view : RANSeq
+2016-08-24 17:27:21,141 DEBUG: Start: Iteration 30
+2016-08-24 17:27:21,162 DEBUG: View 0 : 0.770114942529
+2016-08-24 17:27:21,172 DEBUG: View 1 : 0.522988505747
+2016-08-24 17:27:21,212 DEBUG: View 2 : 0.442528735632
+2016-08-24 17:27:21,221 DEBUG: View 3 : 0.67816091954
+2016-08-24 17:27:21,365 DEBUG: Best view : Methyl
+2016-08-24 17:27:23,483 DEBUG: Start: Iteration 31
+2016-08-24 17:27:23,502 DEBUG: View 0 : 0.540229885057
+2016-08-24 17:27:23,512 DEBUG: View 1 : 0.522988505747
+2016-08-24 17:27:23,552 DEBUG: View 2 : 0.425287356322
+2016-08-24 17:27:23,561 DEBUG: View 3 : 0.5
+2016-08-24 17:27:23,700 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:25,832 DEBUG: Start: Iteration 32
+2016-08-24 17:27:25,851 DEBUG: View 0 : 0.33908045977
+2016-08-24 17:27:25,859 DEBUG: View 1 : 0.695402298851
+2016-08-24 17:27:25,899 DEBUG: View 2 : 0.540229885057
+2016-08-24 17:27:25,907 DEBUG: View 3 : 0.557471264368
+2016-08-24 17:27:26,056 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:28,321 DEBUG: Start: Iteration 33
+2016-08-24 17:27:28,339 DEBUG: View 0 : 0.390804597701
+2016-08-24 17:27:28,348 DEBUG: View 1 : 0.333333333333
+2016-08-24 17:27:28,388 DEBUG: View 2 : 0.672413793103
+2016-08-24 17:27:28,397 DEBUG: View 3 : 0.35632183908
+2016-08-24 17:27:28,544 DEBUG: Best view : RANSeq
+2016-08-24 17:27:30,848 DEBUG: Start: Iteration 34
+2016-08-24 17:27:30,867 DEBUG: View 0 : 0.350574712644
+2016-08-24 17:27:30,876 DEBUG: View 1 : 0.545977011494
+2016-08-24 17:27:30,915 DEBUG: View 2 : 0.689655172414
+2016-08-24 17:27:30,924 DEBUG: View 3 : 0.614942528736
+2016-08-24 17:27:31,075 DEBUG: Best view : RANSeq
+2016-08-24 17:27:33,490 DEBUG: Start: Iteration 35
+2016-08-24 17:27:33,509 DEBUG: View 0 : 0.597701149425
+2016-08-24 17:27:33,518 DEBUG: View 1 : 0.390804597701
+2016-08-24 17:27:33,559 DEBUG: View 2 : 0.413793103448
+2016-08-24 17:27:33,568 DEBUG: View 3 : 0.689655172414
+2016-08-24 17:27:33,727 DEBUG: Best view : Clinic
+2016-08-24 17:27:36,221 DEBUG: Start: Iteration 36
+2016-08-24 17:27:36,240 DEBUG: View 0 : 0.67816091954
+2016-08-24 17:27:36,250 DEBUG: View 1 : 0.270114942529
+2016-08-24 17:27:36,290 DEBUG: View 2 : 0.408045977011
+2016-08-24 17:27:36,299 DEBUG: View 3 : 0.580459770115
+2016-08-24 17:27:36,460 DEBUG: Best view : Methyl
+2016-08-24 17:27:39,010 DEBUG: Start: Iteration 37
+2016-08-24 17:27:39,029 DEBUG: View 0 : 0.390804597701
+2016-08-24 17:27:39,038 DEBUG: View 1 : 0.666666666667
+2016-08-24 17:27:39,077 DEBUG: View 2 : 0.385057471264
+2016-08-24 17:27:39,086 DEBUG: View 3 : 0.511494252874
+2016-08-24 17:27:39,243 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:41,886 DEBUG: Start: Iteration 38
+2016-08-24 17:27:41,904 DEBUG: View 0 : 0.683908045977
+2016-08-24 17:27:41,914 DEBUG: View 1 : 0.67816091954
+2016-08-24 17:27:41,956 DEBUG: View 2 : 0.304597701149
+2016-08-24 17:27:41,965 DEBUG: View 3 : 0.557471264368
+2016-08-24 17:27:42,128 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:44,780 DEBUG: Start: Iteration 39
+2016-08-24 17:27:44,800 DEBUG: View 0 : 0.488505747126
+2016-08-24 17:27:44,809 DEBUG: View 1 : 0.551724137931
+2016-08-24 17:27:44,849 DEBUG: View 2 : 0.563218390805
+2016-08-24 17:27:44,858 DEBUG: View 3 : 0.408045977011
+2016-08-24 17:27:45,028 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:47,765 DEBUG: Start: Iteration 40
+2016-08-24 17:27:47,783 DEBUG: View 0 : 0.534482758621
+2016-08-24 17:27:47,792 DEBUG: View 1 : 0.729885057471
+2016-08-24 17:27:47,832 DEBUG: View 2 : 0.540229885057
+2016-08-24 17:27:47,840 DEBUG: View 3 : 0.540229885057
+2016-08-24 17:27:48,005 DEBUG: Best view : MiRNA_
+2016-08-24 17:27:50,795 DEBUG: Start: Iteration 41
+2016-08-24 17:27:50,813 DEBUG: View 0 : 0.551724137931
+2016-08-24 17:27:50,822 DEBUG: View 1 : 0.465517241379
+2016-08-24 17:27:50,862 DEBUG: View 2 : 0.695402298851
+2016-08-24 17:27:50,870 DEBUG: View 3 : 0.511494252874
+2016-08-24 17:27:51,044 DEBUG: Best view : RANSeq
+2016-08-24 17:27:53,933 DEBUG: Start: Iteration 42
+2016-08-24 17:27:53,952 DEBUG: View 0 : 0.419540229885
+2016-08-24 17:27:53,961 DEBUG: View 1 : 0.287356321839
+2016-08-24 17:27:54,000 DEBUG: View 2 : 0.557471264368
+2016-08-24 17:27:54,008 DEBUG: View 3 : 0.51724137931
+2016-08-24 17:27:54,180 DEBUG: Best view : RANSeq
+2016-08-24 17:27:57,122 DEBUG: Start: Iteration 43
+2016-08-24 17:27:57,140 DEBUG: View 0 : 0.494252873563
+2016-08-24 17:27:57,149 DEBUG: View 1 : 0.689655172414
+2016-08-24 17:27:57,189 DEBUG: View 2 : 0.672413793103
+2016-08-24 17:27:57,197 DEBUG: View 3 : 0.586206896552
+2016-08-24 17:27:57,372 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:00,355 DEBUG: Start: Iteration 44
+2016-08-24 17:28:00,373 DEBUG: View 0 : 0.316091954023
+2016-08-24 17:28:00,382 DEBUG: View 1 : 0.66091954023
+2016-08-24 17:28:00,422 DEBUG: View 2 : 0.632183908046
+2016-08-24 17:28:00,431 DEBUG: View 3 : 0.522988505747
+2016-08-24 17:28:00,608 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:03,684 DEBUG: Start: Iteration 45
+2016-08-24 17:28:03,702 DEBUG: View 0 : 0.362068965517
+2016-08-24 17:28:03,711 DEBUG: View 1 : 0.649425287356
+2016-08-24 17:28:03,751 DEBUG: View 2 : 0.293103448276
+2016-08-24 17:28:03,760 DEBUG: View 3 : 0.454022988506
+2016-08-24 17:28:03,939 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:07,014 DEBUG: Start: Iteration 46
+2016-08-24 17:28:07,032 DEBUG: View 0 : 0.465517241379
+2016-08-24 17:28:07,041 DEBUG: View 1 : 0.385057471264
+2016-08-24 17:28:07,081 DEBUG: View 2 : 0.626436781609
+2016-08-24 17:28:07,089 DEBUG: View 3 : 0.67816091954
+2016-08-24 17:28:07,271 DEBUG: Best view : Clinic
+2016-08-24 17:28:10,416 DEBUG: Start: Iteration 47
+2016-08-24 17:28:10,435 DEBUG: View 0 : 0.488505747126
+2016-08-24 17:28:10,444 DEBUG: View 1 : 0.557471264368
+2016-08-24 17:28:10,483 DEBUG: View 2 : 0.586206896552
+2016-08-24 17:28:10,491 DEBUG: View 3 : 0.390804597701
+2016-08-24 17:28:10,675 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:13,877 DEBUG: Start: Iteration 48
+2016-08-24 17:28:13,896 DEBUG: View 0 : 0.551724137931
+2016-08-24 17:28:13,905 DEBUG: View 1 : 0.66091954023
+2016-08-24 17:28:13,944 DEBUG: View 2 : 0.689655172414
+2016-08-24 17:28:13,952 DEBUG: View 3 : 0.413793103448
+2016-08-24 17:28:14,140 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:17,471 DEBUG: Start: Iteration 49
+2016-08-24 17:28:17,489 DEBUG: View 0 : 0.5
+2016-08-24 17:28:17,498 DEBUG: View 1 : 0.701149425287
+2016-08-24 17:28:17,537 DEBUG: View 2 : 0.379310344828
+2016-08-24 17:28:17,546 DEBUG: View 3 : 0.367816091954
+2016-08-24 17:28:17,737 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:21,092 DEBUG: Start: Iteration 50
+2016-08-24 17:28:21,111 DEBUG: View 0 : 0.454022988506
+2016-08-24 17:28:21,120 DEBUG: View 1 : 0.706896551724
+2016-08-24 17:28:21,159 DEBUG: View 2 : 0.5
+2016-08-24 17:28:21,168 DEBUG: View 3 : 0.586206896552
+2016-08-24 17:28:21,365 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:24,779 DEBUG: Start: Iteration 51
+2016-08-24 17:28:24,798 DEBUG: View 0 : 0.51724137931
+2016-08-24 17:28:24,808 DEBUG: View 1 : 0.724137931034
+2016-08-24 17:28:24,848 DEBUG: View 2 : 0.706896551724
+2016-08-24 17:28:24,857 DEBUG: View 3 : 0.712643678161
+2016-08-24 17:28:25,055 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:28,594 DEBUG: Start: Iteration 52
+2016-08-24 17:28:28,613 DEBUG: View 0 : 0.563218390805
+2016-08-24 17:28:28,622 DEBUG: View 1 : 0.373563218391
+2016-08-24 17:28:28,661 DEBUG: View 2 : 0.568965517241
+2016-08-24 17:28:28,670 DEBUG: View 3 : 0.413793103448
+2016-08-24 17:28:28,872 DEBUG: Best view : RANSeq
+2016-08-24 17:28:32,461 DEBUG: Start: Iteration 53
+2016-08-24 17:28:32,479 DEBUG: View 0 : 0.741379310345
+2016-08-24 17:28:32,488 DEBUG: View 1 : 0.327586206897
+2016-08-24 17:28:32,527 DEBUG: View 2 : 0.557471264368
+2016-08-24 17:28:32,536 DEBUG: View 3 : 0.436781609195
+2016-08-24 17:28:32,740 DEBUG: Best view : Methyl
+2016-08-24 17:28:36,368 DEBUG: Start: Iteration 54
+2016-08-24 17:28:36,386 DEBUG: View 0 : 0.459770114943
+2016-08-24 17:28:36,395 DEBUG: View 1 : 0.373563218391
+2016-08-24 17:28:36,435 DEBUG: View 2 : 0.488505747126
+2016-08-24 17:28:36,444 DEBUG: View 3 : 0.586206896552
+2016-08-24 17:28:36,646 DEBUG: Best view : Clinic
+2016-08-24 17:28:40,331 DEBUG: Start: Iteration 55
+2016-08-24 17:28:40,349 DEBUG: View 0 : 0.522988505747
+2016-08-24 17:28:40,358 DEBUG: View 1 : 0.287356321839
+2016-08-24 17:28:40,397 DEBUG: View 2 : 0.48275862069
+2016-08-24 17:28:40,406 DEBUG: View 3 : 0.304597701149
+2016-08-24 17:28:40,613 DEBUG: Best view : Methyl
+2016-08-24 17:28:44,382 DEBUG: Start: Iteration 56
+2016-08-24 17:28:44,401 DEBUG: View 0 : 0.362068965517
+2016-08-24 17:28:44,410 DEBUG: View 1 : 0.747126436782
+2016-08-24 17:28:44,450 DEBUG: View 2 : 0.534482758621
+2016-08-24 17:28:44,459 DEBUG: View 3 : 0.540229885057
+2016-08-24 17:28:44,672 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:48,498 DEBUG: Start: Iteration 57
+2016-08-24 17:28:48,517 DEBUG: View 0 : 0.695402298851
+2016-08-24 17:28:48,526 DEBUG: View 1 : 0.672413793103
+2016-08-24 17:28:48,564 DEBUG: View 2 : 0.362068965517
+2016-08-24 17:28:48,573 DEBUG: View 3 : 0.390804597701
+2016-08-24 17:28:48,787 DEBUG: Best view : Methyl
+2016-08-24 17:28:52,684 DEBUG: Start: Iteration 58
+2016-08-24 17:28:52,702 DEBUG: View 0 : 0.293103448276
+2016-08-24 17:28:52,711 DEBUG: View 1 : 0.649425287356
+2016-08-24 17:28:52,750 DEBUG: View 2 : 0.390804597701
+2016-08-24 17:28:52,759 DEBUG: View 3 : 0.367816091954
+2016-08-24 17:28:52,975 DEBUG: Best view : MiRNA_
+2016-08-24 17:28:56,925 DEBUG: Start: Iteration 59
+2016-08-24 17:28:56,943 DEBUG: View 0 : 0.471264367816
+2016-08-24 17:28:56,952 DEBUG: View 1 : 0.5
+2016-08-24 17:28:56,992 DEBUG: View 2 : 0.51724137931
+2016-08-24 17:28:57,000 DEBUG: View 3 : 0.350574712644
+2016-08-24 17:28:57,219 DEBUG: Best view : RANSeq
+2016-08-24 17:29:01,240 DEBUG: Start: Iteration 60
+2016-08-24 17:29:01,258 DEBUG: View 0 : 0.494252873563
+2016-08-24 17:29:01,267 DEBUG: View 1 : 0.402298850575
+2016-08-24 17:29:01,306 DEBUG: View 2 : 0.471264367816
+2016-08-24 17:29:01,315 DEBUG: View 3 : 0.614942528736
+2016-08-24 17:29:01,537 DEBUG: Best view : Clinic
+2016-08-24 17:29:05,631 DEBUG: Start: Iteration 61
+2016-08-24 17:29:05,649 DEBUG: View 0 : 0.632183908046
+2016-08-24 17:29:05,658 DEBUG: View 1 : 0.580459770115
+2016-08-24 17:29:05,697 DEBUG: View 2 : 0.419540229885
+2016-08-24 17:29:05,705 DEBUG: View 3 : 0.591954022989
+2016-08-24 17:29:05,931 DEBUG: Best view : Methyl
+2016-08-24 17:29:10,109 DEBUG: Start: Iteration 62
+2016-08-24 17:29:10,128 DEBUG: View 0 : 0.333333333333
+2016-08-24 17:29:10,137 DEBUG: View 1 : 0.591954022989
+2016-08-24 17:29:10,177 DEBUG: View 2 : 0.586206896552
+2016-08-24 17:29:10,186 DEBUG: View 3 : 0.706896551724
+2016-08-24 17:29:10,415 DEBUG: Best view : Clinic
+2016-08-24 17:29:14,649 DEBUG: Start: Iteration 63
+2016-08-24 17:29:14,667 DEBUG: View 0 : 0.419540229885
+2016-08-24 17:29:14,677 DEBUG: View 1 : 0.287356321839
+2016-08-24 17:29:14,716 DEBUG: View 2 : 0.67816091954
+2016-08-24 17:29:14,726 DEBUG: View 3 : 0.586206896552
+2016-08-24 17:29:14,957 DEBUG: Best view : RANSeq
+2016-08-24 17:29:19,251 DEBUG: Start: Iteration 64
+2016-08-24 17:29:19,270 DEBUG: View 0 : 0.408045977011
+2016-08-24 17:29:19,279 DEBUG: View 1 : 0.67816091954
+2016-08-24 17:29:19,318 DEBUG: View 2 : 0.505747126437
+2016-08-24 17:29:19,327 DEBUG: View 3 : 0.551724137931
+2016-08-24 17:29:19,560 DEBUG: Best view : MiRNA_
+2016-08-24 17:29:23,920 DEBUG: Start: Iteration 65
+2016-08-24 17:29:23,939 DEBUG: View 0 : 0.505747126437
+2016-08-24 17:29:23,948 DEBUG: View 1 : 0.557471264368
+2016-08-24 17:29:23,986 DEBUG: View 2 : 0.545977011494
+2016-08-24 17:29:23,995 DEBUG: View 3 : 0.477011494253
+2016-08-24 17:29:24,230 DEBUG: Best view : RANSeq
+2016-08-24 17:29:28,683 DEBUG: Start: Iteration 66
+2016-08-24 17:29:28,702 DEBUG: View 0 : 0.534482758621
+2016-08-24 17:29:28,711 DEBUG: View 1 : 0.626436781609
+2016-08-24 17:29:28,750 DEBUG: View 2 : 0.454022988506
+2016-08-24 17:29:28,759 DEBUG: View 3 : 0.316091954023
+2016-08-24 17:29:29,004 DEBUG: Best view : MiRNA_
+2016-08-24 17:29:33,525 DEBUG: Start: Iteration 67
+2016-08-24 17:29:33,543 DEBUG: View 0 : 0.683908045977
+2016-08-24 17:29:33,552 DEBUG: View 1 : 0.32183908046
+2016-08-24 17:29:33,592 DEBUG: View 2 : 0.563218390805
+2016-08-24 17:29:33,601 DEBUG: View 3 : 0.344827586207
+2016-08-24 17:29:33,845 DEBUG: Best view : Methyl
+2016-08-24 17:29:38,422 DEBUG: Start: Iteration 68
+2016-08-24 17:29:38,440 DEBUG: View 0 : 0.442528735632
+2016-08-24 17:29:38,449 DEBUG: View 1 : 0.419540229885
+2016-08-24 17:29:38,488 DEBUG: View 2 : 0.528735632184
+2016-08-24 17:29:38,497 DEBUG: View 3 : 0.67816091954
+2016-08-24 17:29:38,740 DEBUG: Best view : Clinic
+2016-08-24 17:29:43,435 DEBUG: Start: Iteration 69
+2016-08-24 17:29:43,453 DEBUG: View 0 : 0.459770114943
+2016-08-24 17:29:43,462 DEBUG: View 1 : 0.67816091954
+2016-08-24 17:29:43,501 DEBUG: View 2 : 0.574712643678
+2016-08-24 17:29:43,510 DEBUG: View 3 : 0.655172413793
+2016-08-24 17:29:43,759 DEBUG: Best view : MiRNA_
+2016-08-24 17:29:48,463 DEBUG: Start: Iteration 70
+2016-08-24 17:29:48,481 DEBUG: View 0 : 0.333333333333
+2016-08-24 17:29:48,490 DEBUG: View 1 : 0.66091954023
+2016-08-24 17:29:48,529 DEBUG: View 2 : 0.545977011494
+2016-08-24 17:29:48,538 DEBUG: View 3 : 0.568965517241
+2016-08-24 17:29:48,789 DEBUG: Best view : MiRNA_
+2016-08-24 17:29:53,582 DEBUG: Start: Iteration 71
+2016-08-24 17:29:53,601 DEBUG: View 0 : 0.436781609195
+2016-08-24 17:29:53,610 DEBUG: View 1 : 0.603448275862
+2016-08-24 17:29:53,649 DEBUG: View 2 : 0.448275862069
+2016-08-24 17:29:53,658 DEBUG: View 3 : 0.66091954023
+2016-08-24 17:29:53,910 DEBUG: Best view : Clinic
+2016-08-24 17:29:58,731 DEBUG: Start: Iteration 72
+2016-08-24 17:29:58,750 DEBUG: View 0 : 0.327586206897
+2016-08-24 17:29:58,759 DEBUG: View 1 : 0.706896551724
+2016-08-24 17:29:58,797 DEBUG: View 2 : 0.620689655172
+2016-08-24 17:29:58,806 DEBUG: View 3 : 0.568965517241
+2016-08-24 17:29:59,062 DEBUG: Best view : MiRNA_
+2016-08-24 17:30:03,975 DEBUG: Start: Iteration 73
+2016-08-24 17:30:03,993 DEBUG: View 0 : 0.494252873563
+2016-08-24 17:30:04,002 DEBUG: View 1 : 0.5
+2016-08-24 17:30:04,041 DEBUG: View 2 : 0.310344827586
+2016-08-24 17:30:04,050 DEBUG: View 3 : 0.477011494253
+2016-08-24 17:30:04,310 DEBUG: Best view : MiRNA_
diff --git a/Code/Versions.py b/Code/MonoMutliViewClassifiers/Versions.py
similarity index 100%
rename from Code/Versions.py
rename to Code/MonoMutliViewClassifiers/Versions.py
diff --git a/Code/MonoMutliViewClassifiers/__init__.py b/Code/MonoMutliViewClassifiers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/DecisionTree.py b/Code/Multiview/Fusion/Methods/MonoviewClassifiers/DecisionTree.py
deleted file mode 100644
index ce91729ff7b44ae7cf57c08ff4fae9134568685a..0000000000000000000000000000000000000000
--- a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/DecisionTree.py
+++ /dev/null
@@ -1,11 +0,0 @@
-from sklearn.tree import DecisionTreeClassifier
-
-
-def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
- maxDepth = int(kwargs['0'])
- classifier = DecisionTreeClassifier(max_depth=maxDepth)
- classifier.fit(DATASET, CLASS_LABELS)
- return classifier
-
-def getConfig(config):
- return "\n\t\t- Decision Tree with max_depth : "+config[0]
\ No newline at end of file
diff --git a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/KNN.py b/Code/Multiview/Fusion/Methods/MonoviewClassifiers/KNN.py
deleted file mode 100644
index d8a59153cc66a6b85b6e7101c865880ff2661c85..0000000000000000000000000000000000000000
--- a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/KNN.py
+++ /dev/null
@@ -1,11 +0,0 @@
-from sklearn.neighbors import KNeighborsClassifier
-
-
-def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
- nNeighbors = int(kwargs['0'])
- classifier = KNeighborsClassifier(n_neighbors=nNeighbors)
- classifier.fit(DATASET, CLASS_LABELS)
- return classifier
-
-def getConfig(config):
- return "\n\t\t- K nearest Neighbors with n_neighbors: "+config[0]
\ No newline at end of file
diff --git a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/RandomForest.py b/Code/Multiview/Fusion/Methods/MonoviewClassifiers/RandomForest.py
deleted file mode 100644
index 7ba9b06683d33228420d4eb98344d694603b074c..0000000000000000000000000000000000000000
--- a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/RandomForest.py
+++ /dev/null
@@ -1,12 +0,0 @@
-from sklearn.ensemble import RandomForestClassifier
-
-
-def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
- num_estimators = int(kwargs['0'])
- maxDepth = int(kwargs['1'])
- classifier = RandomForestClassifier(n_estimators=num_estimators, max_depth=maxDepth, n_jobs=NB_CORES)
- classifier.fit(DATASET, CLASS_LABELS)
- return classifier
-
-def getConfig(config):
- return "\n\t\t- Random Forest with num_esimators : "+config[0]+", max_depth : "+config[1]
\ No newline at end of file
diff --git a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/SGD.py b/Code/Multiview/Fusion/Methods/MonoviewClassifiers/SGD.py
deleted file mode 100644
index 072a7a32634fe15ca1d8550b89cea1f03830d089..0000000000000000000000000000000000000000
--- a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/SGD.py
+++ /dev/null
@@ -1,16 +0,0 @@
-from sklearn.linear_model import SGDClassifier
-
-
-def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
- loss = kwargs['0']
- penalty = kwargs['1']
- try:
- alpha = int(kwargs['2'])
- except:
- alpha = 0.15
- classifier = SGDClassifier(loss=loss, penalty=penalty, alpha=alpha)
- classifier.fit(DATASET, CLASS_LABELS)
- return classifier
-
-def getConfig(config):
- return "\n\t\t- SGDClassifier with loss : "+config[0]+", penalty : "+config[1]
\ No newline at end of file
diff --git a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/SVC.py b/Code/Multiview/Fusion/Methods/MonoviewClassifiers/SVC.py
deleted file mode 100644
index 34c4679d7f5bb1a7b09a19f77ee77c8848dcbcb6..0000000000000000000000000000000000000000
--- a/Code/Multiview/Fusion/Methods/MonoviewClassifiers/SVC.py
+++ /dev/null
@@ -1,13 +0,0 @@
-from sklearn.svm import SVC
-
-
-def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs):
- C = int(kwargs['0'])
- kernel = kwargs['1']
- classifier = SVC(C=C, kernel=kernel, probability=True)
- classifier.fit(DATASET, CLASS_LABELS)
- return classifier
-
-
-def getConfig(config):
- return "\n\t\t- SVM with C : "+config[0]+", kernel : "+config[1]
\ No newline at end of file
diff --git a/Code/__init__.py b/Code/__init__.py
index b07b92a447c02ebc85003d45b395665e6f7f5399..7ccf8824aeffdbfda0483e30758ef7d6d81e4132 100644
--- a/Code/__init__.py
+++ b/Code/__init__.py
@@ -1 +1,2 @@
-__all__ = ['FeatExtraction', 'Monoview', 'Multiview']
\ No newline at end of file
+__all__ = ['FeatExtraction', 'Monoview', 'Multiview', 'MonoviewClassifiers']
+from . import FeatExtraction, Monoview, Multiview, MonoviewClassifiers
\ No newline at end of file