diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/run.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/run.py
deleted file mode 100644
index ece77c707c0bf821797f72f106591ddf4178f4fe..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/run.py
+++ /dev/null
@@ -1,8 +0,0 @@
-# coding=utf-8
-import os
-
-os.system(
-    'python ExecClassifMonoView.py -log --name MultiOmicDataset --type hdf5 --feat RNASeq --pathF /home/doob/Téléchargements/Data_multi_omics/ --CL_type DecisionTree --CL_CV 5 --CL_Cores 4 --CL_split 0.5')
-# /donnees/pj_bdd_bbauvin/Data_multi_omics/
-# MiRNA_  RNASeq  Clinic
-#
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/__init__.py b/multiview_platform/MonoMultiViewClassifiers/Multiview/__init__.py
deleted file mode 100644
index 6a2b51c51ee6325f13ce99782867eab995d167a6..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/Multiview/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# # from Code.MonoMultiViewClassifiers.MultiviewClassifiers import Fusion, Mumbo
-# from . import ExecMultiview
-# # from . import Mumbo
-#
-# __all__ = ['Fusion', 'Mumbo']
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/__init__.py b/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/__init__.py
deleted file mode 100644
index c3bcc032d7f2b718168b92493760a0692cba5e3d..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from . import DifficultyFusionModule, analyzeResults
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/analyzeResults.py b/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/analyzeResults.py
deleted file mode 100644
index af44a6fb415aa97cd62c1a52d10dbca3baf3041b..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/analyzeResults.py
+++ /dev/null
@@ -1,21 +0,0 @@
-from ...Multiview import analyzeResults
-
-# Author-Info
-__author__ = "Baptiste Bauvin"
-__status__ = "Prototype"  # Production, Development, Prototype
-
-
-def execute(classifier, trainLabels,
-            testLabels, DATASET,
-            classificationKWARGS, classificationIndices,
-            LABELS_DICTIONARY, views, nbCores, times,
-            name, KFolds,
-            hyperParamSearch, nIter, metrics,
-            viewsIndices, randomState, labels, classifierModule):
-    return analyzeResults.execute(classifier, trainLabels,
-            testLabels, DATASET,
-            classificationKWARGS, classificationIndices,
-            LABELS_DICTIONARY, views, nbCores, times,
-            name, KFolds,
-            hyperParamSearch, nIter, metrics,
-            viewsIndices, randomState, labels, classifierModule)
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/analyzeResults.py b/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/analyzeResults.py
deleted file mode 100644
index af44a6fb415aa97cd62c1a52d10dbca3baf3041b..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/analyzeResults.py
+++ /dev/null
@@ -1,21 +0,0 @@
-from ...Multiview import analyzeResults
-
-# Author-Info
-__author__ = "Baptiste Bauvin"
-__status__ = "Prototype"  # Production, Development, Prototype
-
-
-def execute(classifier, trainLabels,
-            testLabels, DATASET,
-            classificationKWARGS, classificationIndices,
-            LABELS_DICTIONARY, views, nbCores, times,
-            name, KFolds,
-            hyperParamSearch, nIter, metrics,
-            viewsIndices, randomState, labels, classifierModule):
-    return analyzeResults.execute(classifier, trainLabels,
-            testLabels, DATASET,
-            classificationKWARGS, classificationIndices,
-            LABELS_DICTIONARY, views, nbCores, times,
-            name, KFolds,
-            hyperParamSearch, nIter, metrics,
-            viewsIndices, randomState, labels, classifierModule)
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/analyzeResults.py b/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/analyzeResults.py
deleted file mode 100644
index af44a6fb415aa97cd62c1a52d10dbca3baf3041b..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/analyzeResults.py
+++ /dev/null
@@ -1,21 +0,0 @@
-from ...Multiview import analyzeResults
-
-# Author-Info
-__author__ = "Baptiste Bauvin"
-__status__ = "Prototype"  # Production, Development, Prototype
-
-
-def execute(classifier, trainLabels,
-            testLabels, DATASET,
-            classificationKWARGS, classificationIndices,
-            LABELS_DICTIONARY, views, nbCores, times,
-            name, KFolds,
-            hyperParamSearch, nIter, metrics,
-            viewsIndices, randomState, labels, classifierModule):
-    return analyzeResults.execute(classifier, trainLabels,
-            testLabels, DATASET,
-            classificationKWARGS, classificationIndices,
-            LABELS_DICTIONARY, views, nbCores, times,
-            name, KFolds,
-            hyperParamSearch, nIter, metrics,
-            viewsIndices, randomState, labels, classifierModule)
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/__init__.py b/multiview_platform/MonoMultiViewClassifiers/__init__.py
deleted file mode 100644
index cf3772451d0cd072bd85c63925d798f94df00e1b..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/__init__.py
+++ /dev/null
@@ -1,4 +0,0 @@
-from . import ExecClassif, ResultAnalysis, Metrics, MonoviewClassifiers, \
-    Monoview, Multiview, utils, MultiviewClassifiers
-
-__all__ = ['Metrics', 'Monoview', 'MonoviewClassifiers', 'Multiview', 'utils']
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/__init__.py b/multiview_platform/MonoMultiViewClassifiers/utils/__init__.py
deleted file mode 100644
index 842d824c6b28acf620ca3b31f973f2a924bd9415..0000000000000000000000000000000000000000
--- a/multiview_platform/MonoMultiViewClassifiers/utils/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from . import Dataset, execution, HyperParameterSearch, Transformations
diff --git a/multiview_platform/__init__.py b/multiview_platform/__init__.py
index c41ea4a1af1c65845cc047a3626723ef53833812..f91d950e4c0743ea01764c2d899fb6a4c0966e09 100644
--- a/multiview_platform/__init__.py
+++ b/multiview_platform/__init__.py
@@ -2,4 +2,4 @@
 
 __version__ = "0.0.0.0"
 
-from . import MonoMultiViewClassifiers, Tests, Exec, Versions
+from . import mono_multi_view_classifiers, tests, execute, versions
diff --git a/multiview_platform/Exec.py b/multiview_platform/execute.py
similarity index 100%
rename from multiview_platform/Exec.py
rename to multiview_platform/execute.py
diff --git a/multiview_platform/mono_multi_view_classifiers/__init__.py b/multiview_platform/mono_multi_view_classifiers/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc67607717be8c5dbd47cebdb5b9d31ede486341
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/__init__.py
@@ -0,0 +1,4 @@
+from . import exec_classif, result_analysis, metrics, monoview_classifiers, \
+    monoview, multiview, utils, multiview_classifiers
+
+__all__ = ['Metrics', 'Monoview', 'MonoviewClassifiers', 'Multiview', 'utils']
diff --git a/multiview_platform/MonoMultiViewClassifiers/ExecClassif.py b/multiview_platform/mono_multi_view_classifiers/exec_classif.py
similarity index 88%
rename from multiview_platform/MonoMultiViewClassifiers/ExecClassif.py
rename to multiview_platform/mono_multi_view_classifiers/exec_classif.py
index fb3c7605d8938b7bc27c439cdc484f8ec35206c0..464756e1016deffbd7fb4ae9ec1ddb4539f1cffa 100644
--- a/multiview_platform/MonoMultiViewClassifiers/ExecClassif.py
+++ b/multiview_platform/mono_multi_view_classifiers/exec_classif.py
@@ -15,14 +15,14 @@ matplotlib.use(
     'Agg')  # Anti-Grain Geometry C++ library to make a raster (pixel) image of the figure
 
 # Import own modules
-from . import MonoviewClassifiers
-from . import MultiviewClassifiers
-from .Multiview.ExecMultiview import ExecMultiview, ExecMultiview_multicore
-from .Monoview.ExecClassifMonoView import ExecMonoview, ExecMonoview_multicore
-from .utils import GetMultiviewDb as DB
-from .ResultAnalysis import \
+from . import monoview_classifiers
+from . import multiview_classifiers
+from .multiview.exec_multiview import ExecMultiview, ExecMultiview_multicore
+from .monoview.exec_classif_mono_view import ExecMonoview, ExecMonoview_multicore
+from .utils import get_multiview_db as DB
+from .result_analysis import \
     getResults, plot_results_noise  # resultAnalysis, analyzeLabels, analyzeIterResults, analyzeIterLabels, genNamesFromRes,
-from .utils import execution, Dataset, Multiclass
+from .utils import execution, dataset, multiclass
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -53,30 +53,30 @@ def initBenchmark(CL_type, monoviewAlgos, multiviewAlgos, args):
     benchmark : Dictionary of dictionaries
         Dictionary resuming which mono- and multiview algorithms which will be used in the benchmark.
     """
-    benchmark = {"Monoview": {}, "Multiview": {}}
+    benchmark = {"monoview": {}, "multiview": {}}
     allMultiviewPackages = [name for _, name, isPackage
                             in pkgutil.iter_modules(
-            ['./MonoMultiViewClassifiers/MultiviewClassifiers/']) if isPackage]
+            ['./mono_multi_view_classifiers/multiview_classifiers/']) if isPackage]
 
-    if "Monoview" in CL_type:
+    if "monoview" in CL_type:
         if monoviewAlgos == ['']:
-            benchmark["Monoview"] = [name for _, name, isPackage in
+            benchmark["monoview"] = [name for _, name, isPackage in
                                      pkgutil.iter_modules([
-                                                              "./MonoMultiViewClassifiers/MonoviewClassifiers"])
+                                                              "./mono_multi_view_classifiers/monoview_classifiers"])
                                      if not isPackage]
 
         else:
-            benchmark["Monoview"] = monoviewAlgos
+            benchmark["monoview"] = monoviewAlgos
 
-    if "Multiview" in CL_type:
-        benchmark["Multiview"] = {}
+    if "multiview" in CL_type:
+        benchmark["multiview"] = {}
         if multiviewAlgos == [""]:
             algosMutliview = allMultiviewPackages
         else:
             algosMutliview = multiviewAlgos
         for multiviewPackageName in allMultiviewPackages:
             if multiviewPackageName in algosMutliview:
-                multiviewPackage = getattr(MultiviewClassifiers,
+                multiviewPackage = getattr(multiview_classifiers,
                                            multiviewPackageName)
                 multiviewModule = getattr(multiviewPackage,
                                           multiviewPackageName + "Module")
@@ -85,14 +85,14 @@ def initBenchmark(CL_type, monoviewAlgos, multiviewAlgos, args):
     if CL_type == ["Benchmark"]:
         allMonoviewAlgos = [name for _, name, isPackage in
                             pkgutil.iter_modules([
-                                                     './MonoMultiViewClassifiers/MonoviewClassifiers'])
+                                                     './mono_multi_view_classifiers/monoview_classifiers'])
                             if (not isPackage) and name not in ["framework"]]
-        benchmark["Monoview"] = allMonoviewAlgos
-        benchmark["Multiview"] = dict(
+        benchmark["monoview"] = allMonoviewAlgos
+        benchmark["multiview"] = dict(
             (multiviewPackageName, "_") for multiviewPackageName in
             allMultiviewPackages)
         for multiviewPackageName in allMultiviewPackages:
-            multiviewPackage = getattr(MultiviewClassifiers,
+            multiviewPackage = getattr(multiview_classifiers,
                                        multiviewPackageName)
             multiviewModule = getattr(multiviewPackage,
                                       multiviewPackageName + "Module")
@@ -153,20 +153,20 @@ def initMonoviewExps(benchmark, viewsDictionary, nbClass, kwargsInit):
     benchmark : Dictionary of dictionaries
         Dictionary resuming which mono- and multiview algorithms which will be used in the benchmark.
     """
-    argumentDictionaries = {"Monoview": [], "Multiview": []}
-    if benchmark["Monoview"]:
-        argumentDictionaries["Monoview"] = []
+    argumentDictionaries = {"monoview": [], "multiview": []}
+    if benchmark["monoview"]:
+        argumentDictionaries["monoview"] = []
         for viewName, viewIndex in viewsDictionary.items():
-            for classifier in benchmark["Monoview"]:
+            for classifier in benchmark["monoview"]:
                 if multiple_args(classifier, kwargsInit):
-                    argumentDictionaries["Monoview"] += gen_multiple_args_dictionnaries(nbClass, kwargsInit, classifier, viewName, viewIndex)
+                    argumentDictionaries["monoview"] += gen_multiple_args_dictionnaries(nbClass, kwargsInit, classifier, viewName, viewIndex)
                 else:
                     arguments = {
                         "args": {classifier + "KWARGS": dict((key, value[0]) for key, value in kwargsInit[
                             classifier + "KWARGSInit"].items()), "feat": viewName,
                                  "CL_type": classifier, "nbClass": nbClass},
                         "viewIndex": viewIndex}
-                    argumentDictionaries["Monoview"].append(arguments)
+                    argumentDictionaries["monoview"].append(arguments)
     return argumentDictionaries
 
 def multiple_args(classifier, kwargsInit):
@@ -228,24 +228,24 @@ def initMonoviewKWARGS(args, classifiersNames):
 
         For example, for Adaboost, the KWARGS will be `{"n_estimators":<value>, "base_estimator":<value>}`"""
 
-    logging.debug("Start:\t Initializing Monoview classifiers arguments")
+    logging.debug("Start:\t Initializing monoview classifiers arguments")
     monoviewKWARGS = {}
     for classifiersName in classifiersNames:
         try:
-            classifierModule = getattr(MonoviewClassifiers, classifiersName)
+            classifierModule = getattr(monoview_classifiers, classifiersName)
         except AttributeError:
             raise AttributeError(
-                classifiersName + " is not implemented in MonoviewClassifiers, "
-                                  "please specify the name of the file in MonoviewClassifiers")
+                classifiersName + " is not implemented in monoview_classifiers, "
+                                  "please specify the name of the file in monoview_classifiers")
         monoviewKWARGS[
             classifiersName + "KWARGSInit"] = classifierModule.formatCmdArgs(
             args)
-    logging.debug("Done:\t Initializing Monoview classifiers arguments")
+    logging.debug("Done:\t Initializing monoview classifiers arguments")
     return monoviewKWARGS
 
 
 def initKWARGSFunc(args, benchmark):
-    monoviewKWARGS = initMonoviewKWARGS(args, benchmark["Monoview"])
+    monoviewKWARGS = initMonoviewKWARGS(args, benchmark["monoview"])
     return monoviewKWARGS
 
 
@@ -253,11 +253,11 @@ def initMultiviewArguments(args, benchmark, views, viewsIndices,
                            argumentDictionaries, randomState, directory,
                            resultsMonoview, classificationIndices):
     """Used to add each monoview exeperience args to the list of monoview experiences args"""
-    logging.debug("Start:\t Initializing Multiview classifiers arguments")
+    logging.debug("Start:\t Initializing multiview classifiers arguments")
     multiviewArguments = []
-    if "Multiview" in benchmark:
-        for multiviewAlgoName in benchmark["Multiview"]:
-            multiviewPackage = getattr(MultiviewClassifiers, multiviewAlgoName)
+    if "multiview" in benchmark:
+        for multiviewAlgoName in benchmark["multiview"]:
+            multiviewPackage = getattr(multiview_classifiers, multiviewAlgoName)
             mutliviewModule = getattr(multiviewPackage,
                                       multiviewAlgoName + "Module")
 
@@ -267,8 +267,8 @@ def initMultiviewArguments(args, benchmark, views, viewsIndices,
                                                           directory,
                                                           resultsMonoview,
                                                           classificationIndices)
-    argumentDictionaries["Multiview"] = multiviewArguments
-    logging.debug("Start:\t Initializing Multiview classifiers arguments")
+    argumentDictionaries["multiview"] = multiviewArguments
+    logging.debug("Start:\t Initializing multiview classifiers arguments")
     return argumentDictionaries
 
 
@@ -334,7 +334,7 @@ def execOneBenchmark(coreIndex=-1, LABELS_DICTIONARY=None, directory=None,
                                                  classificationIndices, labels,
                                                  LABELS_DICTIONARY, kFolds)
 
-    logging.debug("Start:\t Monoview benchmark")
+    logging.debug("Start:\t monoview benchmark")
     resultsMonoview += [
         ExecMonoview_multicore(directory, args.name, labelsNames,
                                classificationIndices, kFolds,
@@ -343,19 +343,19 @@ def execOneBenchmark(coreIndex=-1, LABELS_DICTIONARY=None, directory=None,
                                hyperParamSearch=hyperParamSearch,
                                metrics=metrics,
                                nIter=args.CL_HPS_iter, **argument)
-        for argument in argumentDictionaries["Monoview"]]
-    logging.debug("Done:\t Monoview benchmark")
+        for argument in argumentDictionaries["monoview"]]
+    logging.debug("Done:\t monoview benchmark")
 
-    logging.debug("Start:\t Multiview arguments initialization")
+    logging.debug("Start:\t multiview arguments initialization")
     argumentDictionaries = initMultiviewArguments(args, benchmark, views,
                                                   viewsIndices,
                                                   argumentDictionaries,
                                                   randomState, directory,
                                                   resultsMonoview,
                                                   classificationIndices)
-    logging.debug("Done:\t Multiview arguments initialization")
+    logging.debug("Done:\t multiview arguments initialization")
 
-    logging.debug("Start:\t Multiview benchmark")
+    logging.debug("Start:\t multiview benchmark")
     resultsMultiview = [
         ExecMultiview_multicore(directory, coreIndex, args.name,
                                 classificationIndices, kFolds, args.type,
@@ -363,8 +363,8 @@ def execOneBenchmark(coreIndex=-1, LABELS_DICTIONARY=None, directory=None,
                                 labels, hyperParamSearch=hyperParamSearch,
                                 metrics=metrics, nIter=args.CL_HPS_iter,
                                 **arguments)
-        for arguments in argumentDictionaries["Multiview"]]
-    logging.debug("Done:\t Multiview benchmark")
+        for arguments in argumentDictionaries["multiview"]]
+    logging.debug("Done:\t multiview benchmark")
 
     return [flag, resultsMonoview + resultsMultiview]
 
@@ -387,8 +387,8 @@ def execOneBenchmark_multicore(nbCores=-1, LABELS_DICTIONARY=None,
                                                  classificationIndices, labels,
                                                  LABELS_DICTIONARY, kFolds)
 
-    logging.debug("Start:\t Monoview benchmark")
-    nbExperiments = len(argumentDictionaries["Monoview"])
+    logging.debug("Start:\t monoview benchmark")
+    nbExperiments = len(argumentDictionaries["monoview"])
     nbMulticoreToDo = int(math.ceil(float(nbExperiments) / nbCores))
     for stepIndex in range(nbMulticoreToDo):
         resultsMonoview += (Parallel(n_jobs=nbCores)(
@@ -399,24 +399,24 @@ def execOneBenchmark_multicore(nbCores=-1, LABELS_DICTIONARY=None,
                                             hyperParamSearch=hyperParamSearch,
                                             metrics=metrics,
                                             nIter=args.CL_HPS_iter,
-                                            **argumentDictionaries["Monoview"][
+                                            **argumentDictionaries["monoview"][
                                                 coreIndex + stepIndex * nbCores])
             for coreIndex in
             range(min(nbCores, nbExperiments - stepIndex * nbCores))))
-    logging.debug("Done:\t Monoview benchmark")
+    logging.debug("Done:\t monoview benchmark")
 
-    logging.debug("Start:\t Multiview arguments initialization")
+    logging.debug("Start:\t multiview arguments initialization")
     argumentDictionaries = initMultiviewArguments(args, benchmark, views,
                                                   viewsIndices,
                                                   argumentDictionaries,
                                                   randomState, directory,
                                                   resultsMonoview,
                                                   classificationIndices)
-    logging.debug("Done:\t Multiview arguments initialization")
+    logging.debug("Done:\t multiview arguments initialization")
 
-    logging.debug("Start:\t Multiview benchmark")
+    logging.debug("Start:\t multiview benchmark")
     resultsMultiview = []
-    nbExperiments = len(argumentDictionaries["Multiview"])
+    nbExperiments = len(argumentDictionaries["multiview"])
     nbMulticoreToDo = int(math.ceil(float(nbExperiments) / nbCores))
     for stepIndex in range(nbMulticoreToDo):
         resultsMultiview += Parallel(n_jobs=nbCores)(
@@ -429,11 +429,11 @@ def execOneBenchmark_multicore(nbCores=-1, LABELS_DICTIONARY=None,
                                              metrics=metrics,
                                              nIter=args.CL_HPS_iter,
                                              **
-                                             argumentDictionaries["Multiview"][
+                                             argumentDictionaries["multiview"][
                                                  stepIndex * nbCores + coreIndex])
             for coreIndex in
             range(min(nbCores, nbExperiments - stepIndex * nbCores)))
-    logging.debug("Done:\t Multiview benchmark")
+    logging.debug("Done:\t multiview benchmark")
 
     return [flag, resultsMonoview + resultsMultiview]
 
@@ -452,8 +452,8 @@ def execOneBenchmarkMonoCore(DATASET=None, LABELS_DICTIONARY=None,
     resultsMonoview, labelsNames = benchmarkInit(directory,
                                                  classificationIndices, labels,
                                                  LABELS_DICTIONARY, kFolds)
-    logging.debug("Start:\t Monoview benchmark")
-    for arguments in argumentDictionaries["Monoview"]:
+    logging.debug("Start:\t monoview benchmark")
+    for arguments in argumentDictionaries["monoview"]:
         X = DATASET.get("View" + str(arguments["viewIndex"]))
         Y = labels
         resultsMonoview += [
@@ -462,9 +462,9 @@ def execOneBenchmarkMonoCore(DATASET=None, LABELS_DICTIONARY=None,
                          1, args.type, args.pathF, randomState,
                          hyperParamSearch=hyperParamSearch, metrics=metrics,
                          nIter=args.CL_HPS_iter, **arguments)]
-    logging.debug("Done:\t Monoview benchmark")
+    logging.debug("Done:\t monoview benchmark")
 
-    logging.debug("Start:\t Multiview arguments initialization")
+    logging.debug("Start:\t multiview arguments initialization")
 
     argumentDictionaries = initMultiviewArguments(args, benchmark, views,
                                                   viewsIndices,
@@ -472,18 +472,18 @@ def execOneBenchmarkMonoCore(DATASET=None, LABELS_DICTIONARY=None,
                                                   randomState, directory,
                                                   resultsMonoview,
                                                   classificationIndices)
-    logging.debug("Done:\t Multiview arguments initialization")
+    logging.debug("Done:\t multiview arguments initialization")
 
-    logging.debug("Start:\t Multiview benchmark")
+    logging.debug("Start:\t multiview benchmark")
     resultsMultiview = []
-    for arguments in argumentDictionaries["Multiview"]:
+    for arguments in argumentDictionaries["multiview"]:
         resultsMultiview += [
             ExecMultiview(directory, DATASET, args.name, classificationIndices,
                           kFolds, 1, args.type,
                           args.pathF, LABELS_DICTIONARY, randomState, labels,
                           hyperParamSearch=hyperParamSearch,
                           metrics=metrics, nIter=args.CL_HPS_iter, **arguments)]
-    logging.debug("Done:\t Multiview benchmark")
+    logging.debug("Done:\t multiview benchmark")
 
     return [flag, resultsMonoview + resultsMultiview]
 
@@ -519,7 +519,7 @@ def execBenchmark(nbCores, statsIter, nbMulticlass,
         indices for the biclass training set, the ones for the biclass testing set and the ones for the
         multiclass testing set.
     metrics : list of lists
-        Metrics that will be used to evaluate the algorithms performance.
+        metrics that will be used to evaluate the algorithms performance.
     labelsDictionary : dictionary
         Dictionary mapping labels indices to labels names.
     nbLabels : int
@@ -618,13 +618,13 @@ def execClassif(arguments):
             splits = execution.genSplits(DATASET.get("Labels").value, args.CL_split,
                                          statsIterRandomStates)
 
-            multiclassLabels, labelsCombinations, indicesMulticlass = Multiclass.genMulticlassLabels(
+            multiclassLabels, labelsCombinations, indicesMulticlass = multiclass.genMulticlassLabels(
                 DATASET.get("Labels").value, multiclassMethod, splits)
 
             kFolds = execution.genKFolds(statsIter, args.CL_nbFolds,
                                          statsIterRandomStates)
 
-            datasetFiles = Dataset.initMultipleDatasets(args.pathF, args.name, nbCores)
+            datasetFiles = dataset.initMultipleDatasets(args.pathF, args.name, nbCores)
 
             # if not views:
             #     raise ValueError("Empty views list, modify selected views to match dataset " + args.views)
@@ -638,7 +638,7 @@ def execClassif(arguments):
             if metrics == [[""]]:
                 metricsNames = [name for _, name, isPackage
                                 in pkgutil.iter_modules(
-                        ['./MonoMultiViewClassifiers/Metrics']) if
+                        ['./mono_multi_view_classifiers/metrics']) if
                                 not isPackage and name not in ["framework", "log_loss",
                                                                "matthews_corrcoef",
                                                                "roc_auc_score"]]
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/__init__.py b/multiview_platform/mono_multi_view_classifiers/metrics/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/accuracy_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/accuracy_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/accuracy_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/accuracy_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/f1_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/f1_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/f1_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/f1_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/fbeta_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/fbeta_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/fbeta_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/fbeta_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/framework.py b/multiview_platform/mono_multi_view_classifiers/metrics/framework.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/framework.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/framework.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/generic_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/generic_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/generic_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/generic_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/hamming_loss.py b/multiview_platform/mono_multi_view_classifiers/metrics/hamming_loss.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/hamming_loss.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/hamming_loss.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/jaccard_similarity_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/jaccard_similarity_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/jaccard_similarity_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/jaccard_similarity_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/log_loss.py b/multiview_platform/mono_multi_view_classifiers/metrics/log_loss.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/log_loss.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/log_loss.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/matthews_corrcoef.py b/multiview_platform/mono_multi_view_classifiers/metrics/matthews_corrcoef.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/matthews_corrcoef.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/matthews_corrcoef.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/precision_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/precision_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/precision_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/precision_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/recall_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/recall_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/recall_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/recall_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/roc_auc_score.py b/multiview_platform/mono_multi_view_classifiers/metrics/roc_auc_score.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/roc_auc_score.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/roc_auc_score.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Metrics/zero_one_loss.py b/multiview_platform/mono_multi_view_classifiers/metrics/zero_one_loss.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Metrics/zero_one_loss.py
rename to multiview_platform/mono_multi_view_classifiers/metrics/zero_one_loss.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/__init__.py b/multiview_platform/mono_multi_view_classifiers/monoview/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/BoostUtils.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/BoostUtils.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CBBoostUtils.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/CBBoostUtils.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CBBoostUtils.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/CBBoostUtils.py
index 38b3ab8740f4068e0478eafcb69932cdd55ec3a3..10137028b9ff226010f0304f3413249a82a005c5 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CBBoostUtils.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/additions/CBBoostUtils.py
@@ -10,8 +10,8 @@ from sklearn.utils.validation import check_is_fitted
 
 from .BoostUtils import StumpsClassifiersGenerator, sign, BaseBoost, \
     getInterpretBase, get_accuracy_graph, TreeClassifiersGenerator
-from ..MonoviewUtils import change_label_to_minus
-from ... import Metrics
+from ..monoview_utils import change_label_to_minus
+from ... import metrics
 
 
 # Used for CBBoost
@@ -20,7 +20,7 @@ class CBBoostClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
     def __init__(self, n_max_iterations=100, estimators_generator="Stumps",
                  random_state=42, self_complemented=True, twice_the_same=True,
                  random_start=False, n_stumps=1, c_bound_sol=True,
-                 plotted_metric=Metrics.zero_one_loss, save_train_data=False,
+                 plotted_metric=metrics.zero_one_loss, save_train_data=False,
                  test_graph=True, mincq_tracking=False):
         super(CBBoostClassifier, self).__init__()
         r"""
@@ -205,7 +205,7 @@ class CBBoostClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
 
         # Used to compute the optimal c-bound distribution on the chose set
         if self.mincq_tracking:
-            from ...MonoviewClassifiers.MinCQ import MinCqLearner
+            from ...monoview_classifiers.min_cq import MinCqLearner
             mincq = MinCqLearner(10e-3, "stumps", n_stumps_per_attribute=1,
                                  self_complemented=False)
             training_set = self.classification_matrix[:, self.chosen_columns_]
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CGDescUtils.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/CGDescUtils.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CGDescUtils.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/CGDescUtils.py
index 3916a4b2b8c17483acbd08f747d9d45be6fbb0e4..80b68a4f57d316d8b46ebb825c1a2e871aa413fc 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CGDescUtils.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/additions/CGDescUtils.py
@@ -10,8 +10,8 @@ from sklearn.utils.validation import check_is_fitted
 
 from .BoostUtils import StumpsClassifiersGenerator, sign, BaseBoost, \
     getInterpretBase, get_accuracy_graph, TreeClassifiersGenerator
-from ..MonoviewUtils import change_label_to_minus
-from ... import Metrics
+from ..monoview_utils import change_label_to_minus
+from ... import metrics
 
 
 # Used for QarBoost and CGreed
@@ -21,7 +21,7 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
                  random_state=42, self_complemented=True, twice_the_same=False,
                  c_bound_choice=True, random_start=True,
                  n_stumps=1, use_r=True, c_bound_sol=True,
-                 plotted_metric=Metrics.zero_one_loss, save_train_data=True,
+                 plotted_metric=metrics.zero_one_loss, save_train_data=True,
                  test_graph=True, mincq_tracking=False):
         super(ColumnGenerationClassifierQar, self).__init__()
         r"""
@@ -223,7 +223,7 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
         self.train_metrics.append(train_metric)
         self.bounds.append(bound)
         if self.mincq_tracking:  # Used to compute the optimal c-bound distribution on the chose set
-            from ...MonoviewClassifiers.MinCQ import MinCqLearner
+            from ...monoview_classifiers.min_cq import MinCqLearner
             mincq = MinCqLearner(10e-3, "stumps", n_stumps_per_attribute=1,
                                  self_complemented=False)
             training_set = self.classification_matrix[:, self.chosen_columns_]
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/CQBoostUtils.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/CQBoostUtils.py
index 6af59377abf2b927f3a2a8d1f77bad34724c914b..06e2175d63d1199c5926cf308bf91600158c29ac 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/additions/CQBoostUtils.py
@@ -12,7 +12,7 @@ from sklearn.utils.validation import check_is_fitted
 
 from .BoostUtils import StumpsClassifiersGenerator, ConvexProgram, sign, \
     BaseBoost, TreeClassifiersGenerator
-from ... import Metrics
+from ... import metrics
 
 
 class ColumnGenerationClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
@@ -26,7 +26,7 @@ class ColumnGenerationClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
         self.dual_constraint_rhs = dual_constraint_rhs
         self.mu = mu
         self.train_time = 0
-        self.plotted_metric = Metrics.zero_one_loss
+        self.plotted_metric = metrics.zero_one_loss
         self.random_state = random_state
 
     def fit(self, X, y):
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/MinCQUtils.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/MinCQUtils.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/MinCQUtils.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/MinCQUtils.py
index 043e095cdc448d1c312ee0dfc234aea5276ba502..d38c9ce10129c69a678abf2524c677b1d9562b26 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/MinCQUtils.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/additions/MinCQUtils.py
@@ -18,7 +18,7 @@ from sklearn.utils.graph import graph_laplacian
 from sklearn.utils.validation import check_X_y
 
 from .BoostUtils import ConvexProgram
-from ..MonoviewUtils import change_label_to_zero, change_label_to_minus
+from ..monoview_utils import change_label_to_zero, change_label_to_minus
 
 
 class MinCqClassifier(VotingClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/PregenUtils.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/PregenUtils.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/PregenUtils.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/PregenUtils.py
index 8e0d327205036ed3fbbfa030e6a455704f6721bc..79b30c5627fcf353d6b3b0fda4cee78181e4e026 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/PregenUtils.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/additions/PregenUtils.py
@@ -1,6 +1,6 @@
 from .BoostUtils import StumpsClassifiersGenerator, BaseBoost, \
     TreeClassifiersGenerator
-from ..MonoviewUtils import change_label_to_minus
+from ..monoview_utils import change_label_to_minus
 
 
 class PregenClassifier(BaseBoost):
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/SVCClassifier.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/SVCClassifier.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/SVCClassifier.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/SVCClassifier.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/__init__.py b/multiview_platform/mono_multi_view_classifiers/monoview/additions/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/_custom_criterion.pxd b/multiview_platform/mono_multi_view_classifiers/monoview/additions/_custom_criterion.pxd
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/_custom_criterion.pxd
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/_custom_criterion.pxd
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/_custom_criterion.pyx b/multiview_platform/mono_multi_view_classifiers/monoview/additions/_custom_criterion.pyx
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/_custom_criterion.pyx
rename to multiview_platform/mono_multi_view_classifiers/monoview/additions/_custom_criterion.pyx
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/analyzeResult.py b/multiview_platform/mono_multi_view_classifiers/monoview/analyzeResult.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/analyzeResult.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/analyzeResult.py
index e293bfc97e898981431d2a982ee80909138d13be..9e6a5db61ddbaf10b31a4dcbadc29c27b44629b3 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/analyzeResult.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/analyzeResult.py
@@ -1,6 +1,6 @@
 from datetime import timedelta as hms
 
-from .. import Metrics
+from .. import metrics
 
 
 def getDBConfigString(name, feat, classificationIndices, shape,
@@ -32,7 +32,7 @@ def getClassifierConfigString(gridSearch, nbCores, nIter, clKWARGS, classifier,
 
 
 def getMetricScore(metric, y_train, y_train_pred, y_test, y_test_pred):
-    metricModule = getattr(Metrics, metric[0])
+    metricModule = getattr(metrics, metric[0])
     if metric[1] is not None:
         metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                             enumerate(metric[1]))
@@ -53,7 +53,7 @@ def execute(name, learningRate, KFolds, nbCores, gridSearch, metrics, nIter,
             shape, y_train, y_train_pred, y_test, y_test_pred, time,
             randomState, classifier, directory):
     metricsScores = {}
-    metricModule = getattr(Metrics, metrics[0][0])
+    metricModule = getattr(metrics, metrics[0][0])
     trainScore = metricModule.score(y_train, y_train_pred)
     testScore = metricModule.score(y_test, y_test_pred)
     stringAnalysis = "Classification on " + name + " database for " + feat + " with " + CL_type + ".\n\n"
@@ -76,8 +76,8 @@ def execute(name, learningRate, KFolds, nbCores, gridSearch, metrics, nIter,
         #     metricKWARGS = dict((index, metricConfig) for index, metricConfig in enumerate(metric[1]))
         # else:
         #     metricKWARGS = {}
-        # metricsScores[metric[0]] = [getattr(Metrics, metric[0]).score(y_train, y_train_pred),
-        #                             getattr(Metrics, metric[0]).score(y_test, y_test_pred)]
+        # metricsScores[metric[0]] = [getattr(metrics, metric[0]).score(y_train, y_train_pred),
+        #                             getattr(metrics, metric[0]).score(y_test, y_test_pred)]
     stringAnalysis += "\n\n Classification took " + str(hms(seconds=int(time)))
     stringAnalysis += "\n\n Classifier Interpretation : \n"
     stringAnalysis += classifierIntepretString
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py b/multiview_platform/mono_multi_view_classifiers/monoview/exec_classif_mono_view.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/exec_classif_mono_view.py
index 0e6890857c8e9b56801acf2d759f1f9ccb00bb32..b38a276f6420eca9a64120d9cc07fe455b754e10 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/exec_classif_mono_view.py
@@ -12,11 +12,11 @@ import h5py
 # Import 3rd party modules
 import numpy as np  # for reading CSV-files and Series
 
-from . import MonoviewUtils
+from . import monoview_utils
 from .analyzeResult import execute
 # Import own modules
-from .. import MonoviewClassifiers
-from ..utils.Dataset import getValue, extractSubset
+from .. import monoview_classifiers
+from ..utils.dataset import getValue, extractSubset
 
 # Author-Info
 __author__ = "Nikolas Huelsmann, Baptiste BAUVIN"
@@ -77,7 +77,7 @@ def ExecMonoview(directory, X, Y, name, labelsNames, classificationIndices,
 
     logging.debug("Start:\t Generate classifier args")
     classifierModuleName = CL_type.split("_")[0]
-    classifierModule = getattr(MonoviewClassifiers, classifierModuleName)
+    classifierModule = getattr(monoview_classifiers, classifierModuleName)
     clKWARGS, testFoldsPreds = getHPs(classifierModule, hyperParamSearch,
                                       nIter, CL_type, X_train, y_train,
                                       randomState, outputFileName,
@@ -108,7 +108,7 @@ def ExecMonoview(directory, X, Y, name, labelsNames, classificationIndices,
     logging.debug(
         "Info:\t Time for training and predicting: " + str(t_end) + "[s]")
 
-    logging.debug("Start:\t Getting Results")
+    logging.debug("Start:\t Getting results")
     stringAnalysis, \
     imagesAnalysis, \
     metricsScores = execute(name, classificationIndices, KFolds, nbCores,
@@ -117,19 +117,19 @@ def ExecMonoview(directory, X, Y, name, labelsNames, classificationIndices,
                             y_train, y_train_pred, y_test, y_test_pred, t_end,
                             randomState, classifier, outputFileName)
     # cl_desc = [value for key, value in sorted(clKWARGS.items())]
-    logging.debug("Done:\t Getting Results")
+    logging.debug("Done:\t Getting results")
 
     logging.debug("Start:\t Saving preds")
     saveResults(stringAnalysis, outputFileName, full_labels_pred, y_train_pred,
                 y_train, imagesAnalysis, y_test)
-    logging.info("Done:\t Saving Results")
+    logging.info("Done:\t Saving results")
 
     viewIndex = args["viewIndex"]
     if testFoldsPreds is None:
         testFoldsPreds = y_train_pred
-    return MonoviewUtils.MonoviewResult(viewIndex, CL_type, feat, metricsScores,
-                                        full_labels_pred, clKWARGS,
-                                        y_test_multiclass_pred, testFoldsPreds)
+    return monoview_utils.MonoviewResult(viewIndex, CL_type, feat, metricsScores,
+                                         full_labels_pred, clKWARGS,
+                                         y_test_multiclass_pred, testFoldsPreds)
     # return viewIndex, [CL_type, feat, metricsScores, full_labels_pred, clKWARGS, y_test_multiclass_pred, testFoldsPreds]
 
 
@@ -150,7 +150,7 @@ def initConstants(args, X, classificationIndices, labelsNames, name, directory):
     labelsString = "-".join(labelsNames)
     CL_type_string = CL_type
     timestr = time.strftime("%Y_%m_%d-%H_%M_%S")
-    outputFileName = directory + CL_type_string + "/" + feat + "/" + timestr + "-Results-" + CL_type_string + "-" + labelsString + \
+    outputFileName = directory + CL_type_string + "/" + feat + "/" + timestr + "-results-" + CL_type_string + "-" + labelsString + \
                      '-learnRate_{0:.2f}'.format(
                          learningRate) + '-' + name + "-" + feat + "-"
     if not os.path.exists(os.path.dirname(outputFileName)):
@@ -182,7 +182,7 @@ def getHPs(classifierModule, hyperParamSearch, nIter, CL_type, X_train, y_train,
         logging.debug(
             "Start:\t " + hyperParamSearch + " best settings with " + str(
                 nIter) + " iterations for " + CL_type)
-        classifierHPSearch = getattr(MonoviewUtils, hyperParamSearch)
+        classifierHPSearch = getattr(monoview_utils, hyperParamSearch)
         clKWARGS, testFoldsPreds = classifierHPSearch(X_train, y_train,
                                                       randomState,
                                                       outputFileName,
@@ -237,7 +237,7 @@ if __name__ == '__main__':
     import argparse
     import pickle
 
-    from ..utils import Dataset
+    from ..utils import dataset
 
     parser = argparse.ArgumentParser(
         description='This methods is used to execute a multiclass classification with one single view. ',
@@ -315,7 +315,7 @@ if __name__ == '__main__':
     databaseType = None
 
     # Extract the data using MPI
-    X, Y = Dataset.getMonoviewShared(path, name, viewName)
+    X, Y = dataset.getMonoviewShared(path, name, viewName)
 
     # Init log
     logFileName = time.strftime(
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecPlot.py b/multiview_platform/mono_multi_view_classifiers/monoview/exec_plot.py
similarity index 90%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/ExecPlot.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/exec_plot.py
index 6be38474597c5a084e905b2a0afd91c9a56cc66b..b09645cb886cd358db578d27c7f412f1331a0530 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecPlot.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/exec_plot.py
@@ -33,7 +33,7 @@
 # args.param = "HSV_V_Bins"
 # args.show = False
 # df_feat_res = pd.DataFrame.from_csv(
-#     path="D:\\BitBucket\\multiview-machine-learning-omis\\Results\\Hydra\\2016_03_23-FPO-Caltech-HSV-HSV_V_Bins.csv",
+#     path="D:\\BitBucket\\multiview-machine-learning-omis\\results\\Hydra\\2016_03_23-FPO-Caltech-HSV-HSV_V_Bins.csv",
 #     sep=';')
 #
 # # Get data from result to show results in plot
@@ -66,7 +66,7 @@
 # # Description of Feature
 # feat_desc = df_feat_res.a_feat_desc.values
 #
-# dir = os.path.dirname(os.path.abspath(__file__)) + "/Results-FeatParaOpt/"
+# dir = os.path.dirname(os.path.abspath(__file__)) + "/results-FeatParaOpt/"
 # # filename = datetime.datetime.now().strftime("%Y_%m_%d") + "-FPO-" + args.name + "-" + args.feature + "-" + args.param
 # # ExportResults.exportPandasToCSV(df_feat_res, directory, filename)
 #
@@ -77,13 +77,13 @@
 #     store = True
 #
 # fileName = datetime.datetime.now().strftime("%Y_%m_%d") + "-FPO-" + args.name + "-" + args.feature + "-" + args.param
-# # Show Results for Calculation
+# # Show results for Calculation
 # ExportResults.showScoreTime(dir, fileName + "-TotalTime", store, score, tot_time, rangeX, args.param, feat_desc,
-#                             cl_desc, 'Results for Parameter Optimisation - DB:' + args.name + ' Feat:' + args.feature,
+#                             cl_desc, 'results for Parameter Optimisation - DB:' + args.name + ' Feat:' + args.feature,
 #                             'Precision', 'Total Time (Feature Extraction+Classification)\n [s]')
 # ExportResults.showScoreTime(dir, fileName + "-FeatExtTime", store, score, feat_time, rangeX, args.param, feat_desc,
-#                             cl_desc, 'Results for Parameter Optimisation - DB:' + args.name + ' Feat:' + args.feature,
+#                             cl_desc, 'results for Parameter Optimisation - DB:' + args.name + ' Feat:' + args.feature,
 #                             'Precision', 'Feature Extraction Time\n [s]')
 # ExportResults.showScoreTime(dir, fileName + "-ClassTime", store, score, cl_time, rangeX, args.param, feat_desc, cl_desc,
-#                             'Results for Parameter Optimisation - DB:' + args.name + ' Feat:' + args.feature,
+#                             'results for Parameter Optimisation - DB:' + args.name + ' Feat:' + args.feature,
 #                             'Precision', 'Classification Time\n [s]')
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExportResults.py b/multiview_platform/mono_multi_view_classifiers/monoview/export_results.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/ExportResults.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/export_results.py
index 086080ee0cb61a7731a533035497a5284b159bdb..b2d969b3c0f30063086c5004bf301e5c35c6b7cb 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExportResults.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/export_results.py
@@ -169,7 +169,7 @@ def showResults(directory, filename, db, feat, score):
     plt.xlabel('ClassLabels')
     plt.ylabel('Precision in %')
     plt.title(
-        'Results of ' + feat + '-Classification\n for ' + db + ' Database')
+        'results of ' + feat + '-Classification\n for ' + db + ' Database')
     plt.axis([0, len(score), 0, 100])
     plt.xticks(range(0, len(score), 5))
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/MonoviewUtils.py b/multiview_platform/mono_multi_view_classifiers/monoview/monoview_utils.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/Monoview/MonoviewUtils.py
rename to multiview_platform/mono_multi_view_classifiers/monoview/monoview_utils.py
index 1d6c41290cc0ec639707df8309953712c36e8b7f..eb36869cea3caa709d51a87bc71198fc8b37665c 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/MonoviewUtils.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/monoview_utils.py
@@ -6,8 +6,8 @@ from matplotlib.ticker import FuncFormatter
 from scipy.stats import uniform, randint
 from sklearn.model_selection import RandomizedSearchCV
 
-from .. import Metrics
-from ..utils import HyperParameterSearch
+from .. import metrics
+from ..utils import hyper_parameter_search
 
 # Author-Info
 __author__ = "Nikolas Huelsmann, Baptiste Bauvin"
@@ -25,7 +25,7 @@ def randomizedSearch(X_train, y_train, randomState, outputFileName,
                                                    **classifier_KWARGS)
     params_dict = estimator.genDistribs()
     if params_dict:
-        metricModule = getattr(Metrics, metric[0])
+        metricModule = getattr(metrics, metric[0])
         if metric[1] is not None:
             metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                                 enumerate(metric[1]))
@@ -51,7 +51,7 @@ def randomizedSearch(X_train, y_train, randomState, outputFileName,
         scoresArray = detector.cv_results_['mean_test_score']
         params = estimator.genParamsFromDetector(detector)
 
-        HyperParameterSearch.genHeatMaps(params, scoresArray, outputFileName)
+        hyper_parameter_search.genHeatMaps(params, scoresArray, outputFileName)
         best_estimator = detector.best_estimator_
     else:
         best_estimator = estimator
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview/run.py b/multiview_platform/mono_multi_view_classifiers/monoview/run.py
new file mode 100644
index 0000000000000000000000000000000000000000..106adb046126d9ecb43987da80aefd9f3c66ca3d
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/run.py
@@ -0,0 +1,8 @@
+# coding=utf-8
+import os
+
+os.system(
+    'python exec_classif_mono_view.py -log --name MultiOmicDataset --type hdf5 --feat RNASeq --pathF /home/doob/Téléchargements/Data_multi_omics/ --CL_type DecisionTree --CL_CV 5 --CL_Cores 4 --CL_split 0.5')
+# /donnees/pj_bdd_bbauvin/Data_multi_omics/
+# MiRNA_  RNASeq  Clinic
+#
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/__init__.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/__init__.py
similarity index 90%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/__init__.py
index be5528d2219a00afdbe16ac9ba088a91306f75be..db257abe4c0afa79fa5166cdd037070aecc6a29e 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/__init__.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/__init__.py
@@ -8,7 +8,7 @@ del module
 del os
 
 """
-To be able to add a Monoview Classifier to the benchmark, one has to :
+To be able to add a monoview Classifier to the benchmark, one has to :
 Create a .py file named after the classifier
 Define a canProbas function returning True or False whether the classifier is able to predict class probabilities
 Define a fit function
@@ -27,5 +27,5 @@ Define a getKWARGS function
     Output :
         KWARGSDict : a dictionnary of arguments matching the kwargs needed in train
 Define a getConfig function that returns a string explaining the algorithm's config using a config dict or list
-Add the arguments to configure the classifier in the parser in ExecClassif.py
+Add the arguments to configure the classifier in the parser in exec_classif.py
 """
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/Adaboost.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/Adaboost.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost.py
index 82b53efa4e1b4765ea1e5d463ecc67c910c901ff..23bbe7185c9cbdc6f68829f42dc73b0eb1fc8464 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/Adaboost.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost.py
@@ -4,9 +4,9 @@ import numpy as np
 from sklearn.ensemble import AdaBoostClassifier
 from sklearn.tree import DecisionTreeClassifier
 
-from .. import Metrics
-from ..Monoview.Additions.BoostUtils import get_accuracy_graph
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier
+from .. import metrics
+from ..monoview.additions.BoostUtils import get_accuracy_graph
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -28,7 +28,7 @@ class Adaboost(AdaBoostClassifier, BaseMonoviewClassifier):
         self.distribs = [CustomRandint(low=1, high=500),
                          [DecisionTreeClassifier(max_depth=1)]]
         self.weird_strings = {"base_estimator": "class_name"}
-        self.plotted_metric = Metrics.zero_one_loss
+        self.plotted_metric = metrics.zero_one_loss
         self.plotted_metric_name = "zero_one_loss"
         self.step_predictions = None
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostGraalpy.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_graalpy.py
similarity index 98%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostGraalpy.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_graalpy.py
index d7ddcab5b48dd543cd45612261c1412cd6b928ad..975bf5ad8a316dedc196d5572654cf94618088ab 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostGraalpy.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_graalpy.py
@@ -4,10 +4,10 @@ import numpy as np
 from sklearn.base import BaseEstimator, ClassifierMixin
 from sklearn.utils.validation import check_is_fitted
 
-from ..Metrics import zero_one_loss
-from ..Monoview.Additions.BoostUtils import StumpsClassifiersGenerator, \
+from ..metrics import zero_one_loss
+from ..monoview.additions.BoostUtils import StumpsClassifiersGenerator, \
     BaseBoost
-from ..Monoview.MonoviewUtils import CustomRandint, \
+from ..monoview.monoview_utils import CustomRandint, \
     BaseMonoviewClassifier, change_label_to_minus, change_label_to_zero
 
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregen.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregen.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen.py
index 07ae58db2946ba9fb7c7514ef581aff1b9a80932..6914c5e79addb0e811269cbff40e285d4c6b2bbc 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregen.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen.py
@@ -4,10 +4,10 @@ import numpy as np
 from sklearn.ensemble import AdaBoostClassifier
 from sklearn.tree import DecisionTreeClassifier
 
-from .. import Metrics
-from ..Monoview.Additions.BoostUtils import get_accuracy_graph
-from ..Monoview.Additions.PregenUtils import PregenClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier, \
+from .. import metrics
+from ..monoview.additions.BoostUtils import get_accuracy_graph
+from ..monoview.additions.PregenUtils import PregenClassifier
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier, \
     change_label_to_zero
 
 # Author-Info
@@ -34,7 +34,7 @@ class AdaboostPregen(AdaBoostClassifier, BaseMonoviewClassifier,
                          [DecisionTreeClassifier(max_depth=1)], [n_stumps],
                          [random_state]]
         self.weird_strings = {"base_estimator": "class_name"}
-        self.plotted_metric = Metrics.zero_one_loss
+        self.plotted_metric = metrics.zero_one_loss
         self.plotted_metric_name = "zero_one_loss"
         self.step_predictions = None
         self.estimators_generator = "Stumps"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregen10.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen10.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregen10.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen10.py
index de729f2dcc63238bb45cc74daef7f4bd777acc1d..d24724ee78a7757357b7c3cd7ca8dfe5b13d4891 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregen10.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen10.py
@@ -1,6 +1,6 @@
 from sklearn.tree import DecisionTreeClassifier
 
-from .AdaboostPregen import AdaboostPregen
+from .adaboost_pregen import AdaboostPregen
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregenTree.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen_tree.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregenTree.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen_tree.py
index fd9401bfa281070ce6c53ba29238f9573b31d744..b5fe62b3a4d79d38c3ab2aecdbcec8b67566bdb0 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/AdaboostPregenTree.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/adaboost_pregen_tree.py
@@ -4,10 +4,10 @@ import numpy as np
 from sklearn.ensemble import AdaBoostClassifier
 from sklearn.tree import DecisionTreeClassifier
 
-from .. import Metrics
-from ..Monoview.Additions.BoostUtils import get_accuracy_graph
-from ..Monoview.Additions.PregenUtils import PregenClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier, \
+from .. import metrics
+from ..monoview.additions.BoostUtils import get_accuracy_graph
+from ..monoview.additions.PregenUtils import PregenClassifier
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier, \
     change_label_to_zero
 
 # Author-Info
@@ -34,7 +34,7 @@ class AdaboostPregenTree(AdaBoostClassifier, BaseMonoviewClassifier,
                          [DecisionTreeClassifier(max_depth=1)], [n_stumps],
                          [random_state], [max_depth]]
         self.weird_strings = {"base_estimator": "class_name"}
-        self.plotted_metric = Metrics.zero_one_loss
+        self.plotted_metric = metrics.zero_one_loss
         self.plotted_metric_name = "zero_one_loss"
         self.step_predictions = None
         self.estimators_generator = "Trees"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGreed.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/c_greed.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGreed.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/c_greed.py
index 6030dc1e44021c7975794c488b12a245f73d8499..dff8a6f3360dcef9528321c24efd5ad33e88dad7 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGreed.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/c_greed.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CGDescUtils import ColumnGenerationClassifierQar
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier, CustomRandint
+from ..monoview.additions.CGDescUtils import ColumnGenerationClassifierQar
+from ..monoview.monoview_utils import BaseMonoviewClassifier, CustomRandint
 
 
 class CGreed(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CBBoost.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cb_boost.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CBBoost.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cb_boost.py
index 4833778269b71e2c4297d3373c9b58a8f1c7e9cd..b7fef9b6367524789b807aa7be5b78b6238a0bae 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CBBoost.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cb_boost.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CBBoostUtils import CBBoostClassifier
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier, CustomRandint
+from ..monoview.additions.CBBoostUtils import CBBoostClassifier
+from ..monoview.monoview_utils import BaseMonoviewClassifier, CustomRandint
 
 
 class CBBoost(CBBoostClassifier, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDesc.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDesc.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc.py
index 30a42f593b5e161ee299e36771e0c2eb215f7f23..62fa41a119be4f21d624fb0767611e9318bb20bd 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDesc.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CGDescUtils import ColumnGenerationClassifierQar
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier, CustomRandint
+from ..monoview.additions.CGDescUtils import ColumnGenerationClassifierQar
+from ..monoview.monoview_utils import BaseMonoviewClassifier, CustomRandint
 
 
 class CGDesc(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDesc10.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc10.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDesc10.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc10.py
index dbc628568ce589609620619e20c701e5f29375aa..229f71c5cf1842b2f515b97135010c8d4795648d 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDesc10.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc10.py
@@ -1,4 +1,4 @@
-from .CGDesc import CGDesc
+from .cg_desc import CGDesc
 
 
 class CGDesc10(CGDesc):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDescTree.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc_tree.py
similarity index 93%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDescTree.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc_tree.py
index bef57eea4567d85b9aa42a518d3ffc59eb7a62b0..d1ab5ee7aea041cb2542c57752eabfea50d63b33 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CGDescTree.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc_tree.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CGDescUtils import ColumnGenerationClassifierQar
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier, CustomRandint
+from ..monoview.additions.CGDescUtils import ColumnGenerationClassifierQar
+from ..monoview.monoview_utils import BaseMonoviewClassifier, CustomRandint
 
 
 class CGDescTree(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoost.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boost.py
similarity index 93%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoost.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boost.py
index 9ed52604f4745fb0f6f05616a654a89da19287b4..aac9472759fe9b6945685b0255760815c48d6cd5 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoost.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boost.py
@@ -1,8 +1,8 @@
 import numpy as np
 
-from ..Monoview.Additions.BoostUtils import getInterpretBase
-from ..Monoview.Additions.CQBoostUtils import ColumnGenerationClassifier
-from ..Monoview.MonoviewUtils import CustomUniform, CustomRandint, \
+from ..monoview.additions.BoostUtils import getInterpretBase
+from ..monoview.additions.CQBoostUtils import ColumnGenerationClassifier
+from ..monoview.monoview_utils import CustomUniform, CustomRandint, \
     BaseMonoviewClassifier
 
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostTree.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boosttree.py
similarity index 93%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostTree.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boosttree.py
index d66eef7675d6e906d4036001b7867a630d27bd87..9cdb2ac5ef740a3e8f79dd9f4c8d6cff0fcfe423 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostTree.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boosttree.py
@@ -1,8 +1,8 @@
 import numpy as np
 
-from ..Monoview.Additions.BoostUtils import getInterpretBase
-from ..Monoview.Additions.CQBoostUtils import ColumnGenerationClassifier
-from ..Monoview.MonoviewUtils import CustomUniform, CustomRandint, \
+from ..monoview.additions.BoostUtils import getInterpretBase
+from ..monoview.additions.CQBoostUtils import ColumnGenerationClassifier
+from ..monoview.monoview_utils import CustomUniform, CustomRandint, \
     BaseMonoviewClassifier
 
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv2.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boostv2.py
similarity index 97%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv2.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boostv2.py
index a308b9baeea0e456ceec5cd3f7d3a8c6388adf69..51fc983da497b185b75d1da59329b33478095a4d 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv2.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boostv2.py
@@ -1,8 +1,8 @@
 import numpy as np
 
-from ..Monoview.Additions.BoostUtils import getInterpretBase
-from ..Monoview.Additions.CQBoostUtils import ColumnGenerationClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, CustomUniform, \
+from ..monoview.additions.BoostUtils import getInterpretBase
+from ..monoview.additions.CQBoostUtils import ColumnGenerationClassifier
+from ..monoview.monoview_utils import CustomRandint, CustomUniform, \
     BaseMonoviewClassifier
 
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv21.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boostv21.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv21.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boostv21.py
index 9875b22a2a480a149df3560a946a5d2d51658e6e..7ccd2168a05c151cc58c4647d64566f529aa0c56 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv21.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boostv21.py
@@ -9,9 +9,9 @@ from sklearn.base import BaseEstimator, ClassifierMixin
 from sklearn.metrics import accuracy_score
 from sklearn.utils.validation import check_is_fitted
 
-from ..Monoview.Additions.BoostUtils import StumpsClassifiersGenerator, sign, \
+from ..monoview.additions.BoostUtils import StumpsClassifiersGenerator, sign, \
     getInterpretBase, BaseBoost
-from ..Monoview.MonoviewUtils import CustomUniform, CustomRandint, \
+from ..monoview.monoview_utils import CustomUniform, CustomRandint, \
     BaseMonoviewClassifier
 
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/DecisionTree.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/decision_tree.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/DecisionTree.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/decision_tree.py
index 4aec553905287fe2b860325d10d5c59b7ca85c23..f108f03e9bb91d54266a14c29156a3c894c6f104 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/DecisionTree.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/decision_tree.py
@@ -1,6 +1,6 @@
 from sklearn.tree import DecisionTreeClassifier
 
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/DecisionTreePregen.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/decision_tree_pregen.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/DecisionTreePregen.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/decision_tree_pregen.py
index 75fa10cc1ef5001674c02c3f842e2ce7dfaa4854..98fa1d1b7e4022b888412f31fb850b014821fd9c 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/DecisionTreePregen.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/decision_tree_pregen.py
@@ -3,8 +3,8 @@ import time
 import numpy as np
 from sklearn.tree import DecisionTreeClassifier
 
-from ..Monoview.Additions.PregenUtils import PregenClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier, \
+from ..monoview.additions.PregenUtils import PregenClassifier
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier, \
     change_label_to_zero
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/GradientBoosting.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/gradient_boosting.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/GradientBoosting.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/gradient_boosting.py
index 8b6acba93ae808025f64109c303085bb1e7489bc..ca1baace9a5b11eb3ca279e36ab883cfcf177eaa 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/GradientBoosting.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/gradient_boosting.py
@@ -4,9 +4,9 @@ import numpy as np
 from sklearn.ensemble import GradientBoostingClassifier
 from sklearn.tree import DecisionTreeClassifier
 
-from .. import Metrics
-from ..Monoview.Additions.BoostUtils import get_accuracy_graph
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier
+from .. import metrics
+from ..monoview.additions.BoostUtils import get_accuracy_graph
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -37,7 +37,7 @@ class GradientBoosting(GradientBoostingClassifier, BaseMonoviewClassifier):
         self.classed_params = []
         self.distribs = [CustomRandint(low=50, high=500), ]
         self.weird_strings = {}
-        self.plotted_metric = Metrics.zero_one_loss
+        self.plotted_metric = metrics.zero_one_loss
         self.plotted_metric_name = "zero_one_loss"
         self.step_predictions = None
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/KNN.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/knn.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/KNN.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/knn.py
index 9774ef7f0cf8c2553b28faf5d4f322d9390efc69..0f7f077914166f78462fbf78d02061d929e8487f 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/KNN.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/knn.py
@@ -1,6 +1,6 @@
 from sklearn.neighbors import KNeighborsClassifier
 
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/Lasso.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/lasso.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/Lasso.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/lasso.py
index 19def37abb8bc1e7c9141f13364cac69eb1cd612..c330f96ee3f81b09bae021f939321ca8a3edf67c 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/Lasso.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/lasso.py
@@ -1,7 +1,7 @@
 import numpy as np
 from sklearn.linear_model import Lasso
 
-from ..Monoview.MonoviewUtils import CustomRandint, CustomUniform, \
+from ..monoview.monoview_utils import CustomRandint, CustomUniform, \
     BaseMonoviewClassifier
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQ.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQ.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq.py
index 620b3ff76d73b7084a4e115ac79928a4d3a57b21..a9421c25bd151e0526b48a47735d9ddbb8ac3a9a 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQ.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq.py
@@ -1,4 +1,4 @@
-from ..Monoview.MonoviewUtils import CustomUniform, BaseMonoviewClassifier
+from ..monoview.monoview_utils import CustomUniform, BaseMonoviewClassifier
 
 #### Algorithm code ####
 
@@ -18,7 +18,7 @@ from sklearn.base import BaseEstimator, ClassifierMixin
 from sklearn.metrics.pairwise import rbf_kernel, linear_kernel, \
     polynomial_kernel
 # from qp import QP
-from ..Monoview.Additions.BoostUtils import ConvexProgram as QP
+from ..monoview.additions.BoostUtils import ConvexProgram as QP
 
 
 # from majority_vote import MajorityVote
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQGraalpy.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq_graalpy.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQGraalpy.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq_graalpy.py
index 7923daec1798bd4cb1dbd21f92b13e6f6bd4e3c1..30b1aff49d3cb9fd5beb75070dfd05f56eb3baac 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQGraalpy.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq_graalpy.py
@@ -1,8 +1,8 @@
 import numpy as np
 
-from ..Monoview.Additions.BoostUtils import StumpsClassifiersGenerator
-from ..Monoview.Additions.MinCQUtils import RegularizedBinaryMinCqClassifier
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier, CustomUniform
+from ..monoview.additions.BoostUtils import StumpsClassifiersGenerator
+from ..monoview.additions.MinCQUtils import RegularizedBinaryMinCqClassifier
+from ..monoview.monoview_utils import BaseMonoviewClassifier, CustomUniform
 
 
 class MinCQGraalpy(RegularizedBinaryMinCqClassifier, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQGraalpyTree.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq_graalpy_tree.py
similarity index 93%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQGraalpyTree.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq_graalpy_tree.py
index b174cbfd87480e80d1f6987277064b1942c58979..c1d399a4ed4035f4968675749b9ac7c0f07e75e5 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/MinCQGraalpyTree.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/min_cq_graalpy_tree.py
@@ -1,8 +1,8 @@
 import numpy as np
 
-from ..Monoview.Additions.BoostUtils import TreeClassifiersGenerator
-from ..Monoview.Additions.MinCQUtils import RegularizedBinaryMinCqClassifier
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier, CustomUniform
+from ..monoview.additions.BoostUtils import TreeClassifiersGenerator
+from ..monoview.additions.MinCQUtils import RegularizedBinaryMinCqClassifier
+from ..monoview.monoview_utils import BaseMonoviewClassifier, CustomUniform
 
 
 class MinCQGraalpyTree(RegularizedBinaryMinCqClassifier,
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoost.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boost.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoost.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boost.py
index e425aa59344fd80f7c6785d5338e46be842ffa38..3723d1dca02948d1b2b6ffc637815b34c0dfc32f 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoost.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boost.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CGDescUtils import ColumnGenerationClassifierQar
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier
+from ..monoview.additions.CGDescUtils import ColumnGenerationClassifierQar
+from ..monoview.monoview_utils import BaseMonoviewClassifier
 
 
 class QarBoost(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC3.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boost_nc3.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC3.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boost_nc3.py
index 98d16a87625c08b79465899e5709c21c4073b7ea..c58921670ff9801848300ed56cf49c38a3b387e0 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC3.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boost_nc3.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CGDescUtils import ColumnGenerationClassifierQar
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier
+from ..monoview.additions.CGDescUtils import ColumnGenerationClassifierQar
+from ..monoview.monoview_utils import BaseMonoviewClassifier
 
 
 class QarBoostNC3(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv2.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boostv2.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv2.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boostv2.py
index 0a083b692f0a98e9b81cc8ee65ba1c548c21b3aa..55d31afdfd7420f4cb48af8ef06e2d3e7efc537b 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv2.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boostv2.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CGDescUtils import ColumnGenerationClassifierQar
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier
+from ..monoview.additions.CGDescUtils import ColumnGenerationClassifierQar
+from ..monoview.monoview_utils import BaseMonoviewClassifier
 
 
 class QarBoostv2(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv3.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boostv3.py
similarity index 91%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv3.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boostv3.py
index c09d380281461c1e62835826f833ca243b365f68..c66c194279025a765b205c9fbf8695890910e98b 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv3.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/qar_boostv3.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.CGDescUtils import ColumnGenerationClassifierQar
-from ..Monoview.MonoviewUtils import BaseMonoviewClassifier
+from ..monoview.additions.CGDescUtils import ColumnGenerationClassifierQar
+from ..monoview.monoview_utils import BaseMonoviewClassifier
 
 
 class QarBoostv3(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/RandomForest.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/random_forest.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/RandomForest.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/random_forest.py
index 2bef1b5f41ae0274238c0ed120c50ddafafbe793..618fa0d07a960f9869b80c00cf17fe2739943c21 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/RandomForest.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/random_forest.py
@@ -1,6 +1,6 @@
 from sklearn.ensemble import RandomForestClassifier
 
-from ..Monoview.MonoviewUtils import CustomRandint, BaseMonoviewClassifier
+from ..monoview.monoview_utils import CustomRandint, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCM.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm.py
similarity index 97%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCM.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm.py
index dc789830cc859d5a6dc2329290a6eeb2b6bb75b0..766f7b06dc4a5ad121a7712f14b4f39f51165ee4 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCM.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm.py
@@ -1,6 +1,6 @@
 from pyscm.scm import SetCoveringMachineClassifier as scm
 
-from ..Monoview.MonoviewUtils import CustomRandint, CustomUniform, \
+from ..monoview.monoview_utils import CustomRandint, CustomUniform, \
     BaseMonoviewClassifier
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregen.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregen.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen.py
index 8f566ba8bd9a4d40c73ee81509af35c70b45b5dc..ae9729b81395c3ae6ea3c715979fd6aa8ef65afb 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregen.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen.py
@@ -3,8 +3,8 @@ import os
 import numpy as np
 from pyscm.scm import SetCoveringMachineClassifier as scm
 
-from ..Monoview.Additions.PregenUtils import PregenClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, CustomUniform, \
+from ..monoview.additions.PregenUtils import PregenClassifier
+from ..monoview.monoview_utils import CustomRandint, CustomUniform, \
     BaseMonoviewClassifier
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregenTree.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen_tree.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregenTree.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen_tree.py
index efb418665735c1a7d1db2a2253959c0666de4f18..a22fa1e28f81d04f44b7e7a2a05d02bf2bfc80f1 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregenTree.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_pregen_tree.py
@@ -3,8 +3,8 @@ import os
 import numpy as np
 from pyscm.scm import SetCoveringMachineClassifier as scm
 
-from ..Monoview.Additions.PregenUtils import PregenClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, CustomUniform, \
+from ..monoview.additions.PregenUtils import PregenClassifier
+from ..monoview.monoview_utils import CustomRandint, CustomUniform, \
     BaseMonoviewClassifier
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsity.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_sparsity.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsity.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_sparsity.py
index c2bdb32b31bdcd41fd69dd75da93900a122b763a..b5d02d90c34f8e0db03e7a881c2f56d077d3d082 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsity.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_sparsity.py
@@ -4,9 +4,9 @@ import time
 import numpy as np
 from pyscm.scm import SetCoveringMachineClassifier as scm
 
-from ..Metrics import zero_one_loss
-from ..Monoview.Additions.PregenUtils import PregenClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, CustomUniform, \
+from ..metrics import zero_one_loss
+from ..monoview.additions.PregenUtils import PregenClassifier
+from ..monoview.monoview_utils import CustomRandint, CustomUniform, \
     BaseMonoviewClassifier
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsityTree.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_sparsity_ttee.py
similarity index 96%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsityTree.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_sparsity_ttee.py
index 3071c5ca55f8f3b090120cc44041e1c3fc28d89c..fdd5491c48a7fdf2b049673de80ba78b1fe734e1 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsityTree.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/scm_sparsity_ttee.py
@@ -4,9 +4,9 @@ import time
 import numpy as np
 from pyscm.scm import SetCoveringMachineClassifier as scm
 
-from ..Metrics import zero_one_loss
-from ..Monoview.Additions.PregenUtils import PregenClassifier
-from ..Monoview.MonoviewUtils import CustomRandint, CustomUniform, \
+from ..metrics import zero_one_loss
+from ..monoview.additions.PregenUtils import PregenClassifier
+from ..monoview.monoview_utils import CustomRandint, CustomUniform, \
     BaseMonoviewClassifier
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SGD.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/sgd.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SGD.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/sgd.py
index a1d3d50266a43797ddc324b6fa6a3674c5976057..dce9fa5a55471472c63b81e8cd27efc97be300a8 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SGD.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/sgd.py
@@ -1,6 +1,6 @@
 from sklearn.linear_model import SGDClassifier
 
-from ..Monoview.MonoviewUtils import CustomUniform, BaseMonoviewClassifier
+from ..monoview.monoview_utils import CustomUniform, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMLinear.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_linear.py
similarity index 85%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMLinear.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_linear.py
index 4eb427b682e62a9dcc7498cadcc8aceac18af2b0..7d7bcd610a6548b4519afb8c357e364d8e2722aa 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMLinear.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_linear.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.SVCClassifier import SVCClassifier
-from ..Monoview.MonoviewUtils import CustomUniform, BaseMonoviewClassifier
+from ..monoview.additions.SVCClassifier import SVCClassifier
+from ..monoview.monoview_utils import CustomUniform, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMPoly.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_poly.py
similarity index 88%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMPoly.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_poly.py
index a5154599990dd1f9230144f793a1ad88cc453bca..b9893492a995914b66b76a7a6988e9d3f364f580 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMPoly.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_poly.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.SVCClassifier import SVCClassifier
-from ..Monoview.MonoviewUtils import CustomUniform, CustomRandint, \
+from ..monoview.additions.SVCClassifier import SVCClassifier
+from ..monoview.monoview_utils import CustomUniform, CustomRandint, \
     BaseMonoviewClassifier
 
 # Author-Info
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMRBF.py b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_rbf.py
similarity index 85%
rename from multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMRBF.py
rename to multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_rbf.py
index 8e8e8d03b6e42dc19b5939b097caa0d75b146675..49edfacce2373faeafac5e9b04f2e9d8f8d90dc8 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SVMRBF.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview_classifiers/svm_rbf.py
@@ -1,5 +1,5 @@
-from ..Monoview.Additions.SVCClassifier import SVCClassifier
-from ..Monoview.MonoviewUtils import CustomUniform, BaseMonoviewClassifier
+from ..monoview.additions.SVCClassifier import SVCClassifier
+from ..monoview.monoview_utils import CustomUniform, BaseMonoviewClassifier
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/Additions/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview/Additions/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Multiview/Additions/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview/Additions/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/Additions/diversity_utils.py b/multiview_platform/mono_multi_view_classifiers/multiview/Additions/diversity_utils.py
similarity index 98%
rename from multiview_platform/MonoMultiViewClassifiers/Multiview/Additions/diversity_utils.py
rename to multiview_platform/mono_multi_view_classifiers/multiview/Additions/diversity_utils.py
index fce99c308b91c42fffc622b636a953dd447f7071..977730184b0f502af77fe4d0025e37d869eddccd 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Multiview/Additions/diversity_utils.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/Additions/diversity_utils.py
@@ -4,7 +4,7 @@ import os
 
 import numpy as np
 
-from ...utils.Multiclass import isBiclass, genMulticlassMonoviewDecision
+from ...utils.multiclass import isBiclass, genMulticlassMonoviewDecision
 
 
 def getClassifiersDecisions(allClassifersNames, viewsIndices, resultsMonoview):
@@ -202,17 +202,17 @@ def getArgs(args, benchmark, views, viewsIndices, randomState,
         foldsGroundTruth = getFoldsGroundTruth(directory, folds=True)
     else:
         foldsGroundTruth = getFoldsGroundTruth(directory, folds=False)
-    monoviewClassifierModulesNames = benchmark["Monoview"]
+    monoviewClassifierModulesNames = benchmark["monoview"]
     classifiersDecisions, classifiersNames = getClassifiersDecisions(
         monoviewClassifierModulesNames,
         viewsIndices,
         resultsMonoview)
-    if name in ['DisagreeFusion', 'DoubleFaultFusion']:
+    if name in ['disagree_fusion', 'double_fault_fusion']:
         classifiersNames, div_measure = couple_div_measure(classifiersNames,
                                                            classifiersDecisions,
                                                            measurement,
                                                            foldsGroundTruth)
-    elif name == "PseudoCQFusion":
+    elif name == "pseudo_cq_fusion":
         classifiersNames, div_measure = CQ_div_measure(classifiersNames,
                                                        classifiersDecisions,
                                                        measurement,
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..a3ab07f2a12aedb7ffa60628a0103c838e9af55b
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/__init__.py
@@ -0,0 +1,5 @@
+# # from Code.mono_multi_view_classifiers.multiview_classifiers import fusion, Mumbo
+# from . import ExecMultiview
+# # from . import Mumbo
+#
+# __all__ = ['fusion', 'Mumbo']
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview/analyzeResults.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/Multiview/analyzeResults.py
rename to multiview_platform/mono_multi_view_classifiers/multiview/analyzeResults.py
index bd06d7f27ef3792ac2595db77ff6a4632db6ab02..0deca9b6c96419d815de93a6d585385fefee6e40 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Multiview/analyzeResults.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/analyzeResults.py
@@ -1,4 +1,4 @@
-from .. import Metrics
+from .. import metrics
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -8,7 +8,7 @@ __status__ = "Prototype"  # Production, Development, Prototype
 def printMetricScore(metricScores, metrics):
     metricScoreString = "\n\n"
     for metric in metrics:
-        metricModule = getattr(Metrics, metric[0])
+        metricModule = getattr(metrics, metric[0])
         if metric[1] is not None:
             metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                                 enumerate(metric[1]))
@@ -26,7 +26,7 @@ def printMetricScore(metricScores, metrics):
 
 def getTotalMetricScores(metric, trainLabels, testLabels, validationIndices,
                          learningIndices, labels):
-    metricModule = getattr(Metrics, metric[0])
+    metricModule = getattr(metrics, metric[0])
     if metric[1] is not None:
         metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                             enumerate(metric[1]))
@@ -67,7 +67,7 @@ def execute(classifier, trainLabels,
     CLASS_LABELS = labels
     learningIndices, validationIndices, testIndicesMulticlass = classificationIndices
 
-    metricModule = getattr(Metrics, metrics[0][0])
+    metricModule = getattr(metrics, metrics[0][0])
     if metrics[0][1] is not None:
         metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                             enumerate(metrics[0][1]))
@@ -81,7 +81,7 @@ def execute(classifier, trainLabels,
 
     classifierConfiguration = classifier.getConfigString(classificationKWARGS)
 
-    stringAnalysis = "\t\tResult for Multiview classification with " + classifierNameString + \
+    stringAnalysis = "\t\tResult for multiview classification with " + classifierNameString + \
                      "\n\n" + metrics[0][0] + " :\n\t-On Train : " + str(
         scoreOnTrain) + "\n\t-On Test : " + str(
         scoreOnTest) + \
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/ExecMultiview.py b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
similarity index 90%
rename from multiview_platform/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
rename to multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
index 54cd4e8585dccb29b8f0b3cf6fffd33d6a2784d0..c6eaf6e83d437c1a699e28b278c11a0aa8bdc59d 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
@@ -7,10 +7,10 @@ import time
 import h5py
 import numpy as np
 
-from .MultiviewUtils import MultiviewResult
-from .. import MultiviewClassifiers
-from ..utils import HyperParameterSearch
-from ..utils.Dataset import getShape
+from .multiview_utils import MultiviewResult
+from .. import multiview_classifiers
+from ..utils import hyper_parameter_search
+from ..utils.dataset import getShape
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -50,7 +50,7 @@ def saveResults(LABELS_DICTIONARY, stringAnalysis, views, classifierModule,
     labelsString = "-".join(labelsSet)
     timestr = time.strftime("%Y_%m_%d-%H_%M_%S")
     CL_type_string = classifierModule.genName(classificationKWARGS)
-    outputFileName = directory + "/" + CL_type_string + "/" + timestr + "-Results-" + CL_type_string + "-" + viewsString + '-' + labelsString + \
+    outputFileName = directory + "/" + CL_type_string + "/" + timestr + "-results-" + CL_type_string + "-" + viewsString + '-' + labelsString + \
                      '-learnRate_{0:.2f}'.format(learningRate) + '-' + name
     if not os.path.exists(os.path.dirname(outputFileName)):
         try:
@@ -113,7 +113,7 @@ def ExecMultiview(directory, DATASET, name, classificationIndices, KFolds,
     logging.debug("Done:\t Getting train/test split")
 
     logging.debug("Start:\t Getting classifiers modules")
-    classifierPackage = getattr(MultiviewClassifiers,
+    classifierPackage = getattr(multiview_classifiers,
                                 CL_type)  # Permet d'appeler un module avec une string
     classifierModule = getattr(classifierPackage, CL_type + "Module")
     classifierClass = getattr(classifierModule, CL_type + "Class")
@@ -122,16 +122,16 @@ def ExecMultiview(directory, DATASET, name, classificationIndices, KFolds,
 
     logging.debug("Start:\t Optimizing hyperparameters")
     if hyperParamSearch != "None":
-        classifier = HyperParameterSearch.searchBestSettings(DATASET, labels,
-                                                             classifierPackage,
-                                                             CL_type, metrics,
-                                                             learningIndices,
-                                                             KFolds,
-                                                             randomState,
-                                                             viewsIndices=viewsIndices,
-                                                             searchingTool=hyperParamSearch,
-                                                             nIter=nIter,
-                                                             **classificationKWARGS)
+        classifier = hyper_parameter_search.searchBestSettings(DATASET, labels,
+                                                               classifierPackage,
+                                                               CL_type, metrics,
+                                                               learningIndices,
+                                                               KFolds,
+                                                               randomState,
+                                                               viewsIndices=viewsIndices,
+                                                               searchingTool=hyperParamSearch,
+                                                               nIter=nIter,
+                                                               **classificationKWARGS)
     else:
         classifier = classifierClass(randomState, NB_CORES=nbCores,
                                      **classificationKWARGS)
@@ -209,10 +209,10 @@ if __name__ == "__main__":
                                default='View0')
     groupStandard.add_argument('--pathF', metavar='STRING', action='store',
                                help='Path to the views (default: %(default)s)',
-                               default='Results-FeatExtr/')
+                               default='results-FeatExtr/')
     groupStandard.add_argument('--directory', metavar='STRING', action='store',
                                help='Path to the views (default: %(default)s)',
-                               default='Results-FeatExtr/')
+                               default='results-FeatExtr/')
     groupStandard.add_argument('--LABELS_DICTIONARY', metavar='STRING',
                                action='store', nargs='+',
                                help='Name of classLabels CSV-file  (default: %(default)s)',
@@ -233,7 +233,7 @@ if __name__ == "__main__":
                                default='randomizedSearch')
     groupStandard.add_argument('--metrics', metavar='STRING', action='store',
                                nargs="+",
-                               help='Metrics used in the experimentation, the first will be the one used in CV',
+                               help='metrics used in the experimentation, the first will be the one used in CV',
                                default=[''])
     groupStandard.add_argument('--nIter', metavar='INT', action='store',
                                help='Number of itetarion in hyper parameter search',
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/MultiviewUtils.py b/multiview_platform/mono_multi_view_classifiers/multiview/multiview_utils.py
similarity index 87%
rename from multiview_platform/MonoMultiViewClassifiers/Multiview/MultiviewUtils.py
rename to multiview_platform/mono_multi_view_classifiers/multiview/multiview_utils.py
index 1bc415bf0ac4a9fc1b57116944bbc0c7476ae5b3..724900fe3dca82577dfc38c1662da4fcaa7fa2a8 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Multiview/MultiviewUtils.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/multiview_utils.py
@@ -1,4 +1,4 @@
-from .. import MultiviewClassifiers
+from .. import multiview_classifiers
 
 
 class MultiviewResult(object):
@@ -11,7 +11,7 @@ class MultiviewResult(object):
         self.y_test_multiclass_pred = test_labels_multiclass
 
     def get_classifier_name(self):
-        multiviewClassifierPackage = getattr(MultiviewClassifiers,
+        multiviewClassifierPackage = getattr(multiview_classifiers,
                                              self.classifier_name)
         multiviewClassifierModule = getattr(multiviewClassifierPackage,
                                             self.classifier_name + "Module")
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/profile b/multiview_platform/mono_multi_view_classifiers/multiview/profile
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/Multiview/profile
rename to multiview_platform/mono_multi_view_classifiers/multiview/profile
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/__init__.py
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..5c0d0a9eb5152a3f5c88ac99fd0fc83b1982873f
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/__init__.py
@@ -0,0 +1 @@
+from . import difficulty_fusion, analyze_results
\ No newline at end of file
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/analyze_results.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/analyze_results.py
new file mode 100644
index 0000000000000000000000000000000000000000..7773f1dcec38f4aba808ec6fc8bd8aa806af1230
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/analyze_results.py
@@ -0,0 +1,21 @@
+from ...multiview import analyzeResults
+
+# Author-Info
+__author__ = "Baptiste Bauvin"
+__status__ = "Prototype"  # Production, Development, Prototype
+
+
+def execute(classifier, trainLabels,
+            testLabels, DATASET,
+            classificationKWARGS, classificationIndices,
+            LABELS_DICTIONARY, views, nbCores, times,
+            name, KFolds,
+            hyperParamSearch, nIter, metrics,
+            viewsIndices, randomState, labels, classifierModule):
+    return analyzeResults.execute(classifier, trainLabels,
+            testLabels, DATASET,
+            classificationKWARGS, classificationIndices,
+            LABELS_DICTIONARY, views, nbCores, times,
+            name, KFolds,
+            hyperParamSearch, nIter, metrics,
+            viewsIndices, randomState, labels, classifierModule)
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/DifficultyFusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/difficulty_fusion.py
similarity index 89%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/DifficultyFusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/difficulty_fusion.py
index 54a130ab871557da808405f5372042cc1e44a7e3..5d33140d74fcc69a88e8590e7510c3bc20a30b0d 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/DifficultyFusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/difficulty_fusion/difficulty_fusion.py
@@ -1,14 +1,14 @@
 import numpy as np
 
-from ...Multiview.Additions import diversity_utils
+from ...multiview.Additions import diversity_utils
 
 
 def genName(config):
-    return "DifficultyFusion"
+    return "difficulty_fusion"
 
 
 def getBenchmark(benchmark, args=None):
-    benchmark["Multiview"]["DifficultyFusion"] = ["take_everything"]
+    benchmark["multiview"]["difficulty_fusion"] = ["take_everything"]
     return benchmark
 
 
@@ -35,7 +35,7 @@ def getArgs(args, benchmark, views, viewsIndices, randomState, directory, result
     return diversity_utils.getArgs(args, benchmark, views,
                                    viewsIndices, randomState, directory,
                                    resultsMonoview, classificationIndices,
-                                   difficulty, "DifficultyFusion")
+                                   difficulty, "difficulty_fusion")
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/DisagreeFusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/DisagreeFusionModule.py
similarity index 90%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/DisagreeFusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/DisagreeFusionModule.py
index e0a7e84ef938a47efccedc6b6142238a985037bc..4ff796b42e8e710cb6d61a65663e63c6dc333a58 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/DisagreeFusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/DisagreeFusionModule.py
@@ -1,14 +1,14 @@
 import numpy as np
 
-from ...Multiview.Additions import diversity_utils
+from ...multiview.Additions import diversity_utils
 
 
 def genName(config):
-    return "DisagreeFusion"
+    return "disagree_fusion"
 
 
 def getBenchmark(benchmark, args=None):
-    benchmark["Multiview"]["DisagreeFusion"] = ["take_everything"]
+    benchmark["multiview"]["disagree_fusion"] = ["take_everything"]
     return benchmark
 
 
@@ -19,7 +19,7 @@ def disagree(classifierDecision1, classifierDecision2, ground_truth):
 def getArgs(args, benchmark, views, viewsIndices, randomState, directory, resultsMonoview, classificationIndices):
     return diversity_utils.getArgs(args, benchmark, views, viewsIndices,
                                    randomState, directory, resultsMonoview,
-                                   classificationIndices, disagree, "DisagreeFusion")
+                                   classificationIndices, disagree, "disagree_fusion")
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/analyzeResults.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/analyzeResults.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/analyzeResults.py
index af44a6fb415aa97cd62c1a52d10dbca3baf3041b..7773f1dcec38f4aba808ec6fc8bd8aa806af1230 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DifficultyFusion/analyzeResults.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/disagree_fusion/analyzeResults.py
@@ -1,4 +1,4 @@
-from ...Multiview import analyzeResults
+from ...multiview import analyzeResults
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/DoubleFaultFusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/DoubleFaultFusionModule.py
similarity index 85%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/DoubleFaultFusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/DoubleFaultFusionModule.py
index 4ed17d2403863473eb176d90f957ae31070b95ba..fceafcf644567a919eaffc5038d70f805edf4b6e 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/DoubleFaultFusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/DoubleFaultFusionModule.py
@@ -1,14 +1,14 @@
 import numpy as np
 
-from ...Multiview.Additions import diversity_utils
+from ...multiview.Additions import diversity_utils
 
 
 def genName(config):
-    return "DoubleFaultFusion"
+    return "double_fault_fusion"
 
 
 def getBenchmark(benchmark, args=None):
-    benchmark["Multiview"]["DoubleFaultFusion"] = ["take_everything"]
+    benchmark["multiview"]["double_fault_fusion"] = ["take_everything"]
     return benchmark
 
 
@@ -21,7 +21,7 @@ def getArgs(args, benchmark, views, viewsIndices, randomState, directory, result
     return diversity_utils.getArgs(args, benchmark, views,
                                    viewsIndices, randomState, directory,
                                    resultsMonoview, classificationIndices,
-                                   doubleFault, "DoubleFaultFusion")
+                                   doubleFault, "double_fault_fusion")
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/analyzeResults.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/analyzeResults.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/analyzeResults.py
index af44a6fb415aa97cd62c1a52d10dbca3baf3041b..7773f1dcec38f4aba808ec6fc8bd8aa806af1230 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/analyzeResults.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/double_fault_fusion/analyzeResults.py
@@ -1,4 +1,4 @@
-from ...Multiview import analyzeResults
+from ...multiview import analyzeResults
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/EntropyFusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/EntropyFusionModule.py
similarity index 89%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/EntropyFusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/EntropyFusionModule.py
index 1f5995e57acd804e3eba404340da7e6010b5e79b..3e83eff5c1eac7ad258daae3dbb5b9c7a27373ec 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/EntropyFusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/EntropyFusionModule.py
@@ -1,14 +1,14 @@
 import numpy as np
 
-from ...Multiview.Additions import diversity_utils
+from ...multiview.Additions import diversity_utils
 
 
 def genName(config):
-    return "EntropyFusion"
+    return "entropy_fusion"
 
 
 def getBenchmark(benchmark, args=None):
-    benchmark["Multiview"]["EntropyFusion"] = ["take_everything"]
+    benchmark["multiview"]["entropy_fusion"] = ["take_everything"]
     return benchmark
 
 
@@ -30,7 +30,7 @@ def getArgs(args, benchmark, views, viewsIndices, randomState, directory, result
     return diversity_utils.getArgs(args, benchmark, views,
                                    viewsIndices, randomState, directory,
                                    resultsMonoview, classificationIndices,
-                                   entropy, "EntropyFusion")
+                                   entropy, "entropy_fusion")
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/EntropyFusion/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/analyzeResults.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/analyzeResults.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/analyzeResults.py
index af44a6fb415aa97cd62c1a52d10dbca3baf3041b..7773f1dcec38f4aba808ec6fc8bd8aa806af1230 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DoubleFaultFusion/analyzeResults.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/entropy_fusion/analyzeResults.py
@@ -1,4 +1,4 @@
-from ...Multiview import analyzeResults
+from ...multiview import analyzeResults
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/FatLateFusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/FatLateFusionModule.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/FatLateFusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/FatLateFusionModule.py
index 717ca70f13e47b70a03abc7d0f3872ad4de0386a..041b679c0a948c2d5f39b22a1d929168e82e7e84 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/FatLateFusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/FatLateFusionModule.py
@@ -1,14 +1,14 @@
 import numpy as np
 
-from ...utils.Multiclass import isBiclass, genMulticlassMonoviewDecision
+from ...utils.multiclass import isBiclass, genMulticlassMonoviewDecision
 
 
 def genName(config):
-    return "FatLateFusion"
+    return "fat_late_fusion"
 
 
 def getBenchmark(benchmark, args=None):
-    benchmark["Multiview"]["FatLateFusion"] = ["take_everything"]
+    benchmark["multiview"]["fat_late_fusion"] = ["take_everything"]
     return benchmark
 
 
@@ -23,7 +23,7 @@ def getArgs(args, benchmark, views, viewsIndices, randomState, directory, result
         weights = [1.0 for _ in range(monoviewDecisions.shape[0])]
     else:
         weights = args.FLF_weights
-    arguments = {"CL_type": "FatLateFusion",
+    arguments = {"CL_type": "fat_late_fusion",
                  "views": views,
                  "NB_VIEW": len(resultsMonoview),
                  "viewsIndices": range(len(resultsMonoview)),
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatLateFusion/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/analyzeResults.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/analyzeResults.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/analyzeResults.py
index af44a6fb415aa97cd62c1a52d10dbca3baf3041b..7773f1dcec38f4aba808ec6fc8bd8aa806af1230 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/DisagreeFusion/analyzeResults.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_late_fusion/analyzeResults.py
@@ -1,4 +1,4 @@
-from ...Multiview import analyzeResults
+from ...multiview import analyzeResults
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/FatSCMLateFusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/FatSCMLateFusionModule.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/FatSCMLateFusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/FatSCMLateFusionModule.py
index fdc0ab700dffd5889ed4217ecbb230d443bab83a..205b360e2dc105bb3438ad4792df386ab3696a6c 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/FatSCMLateFusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/FatSCMLateFusionModule.py
@@ -4,14 +4,14 @@ from sklearn.base import BaseEstimator, ClassifierMixin
 from sklearn.externals.six import iteritems
 
 
-from ...utils.Multiclass import isBiclass, genMulticlassMonoviewDecision
+from ...utils.multiclass import isBiclass, genMulticlassMonoviewDecision
 
 def genName(config):
-    return "FatSCMLateFusion"
+    return "fat_scm_late_fusion"
 
 
 def getBenchmark(benchmark, args=None):
-    benchmark["Multiview"]["FatSCMLateFusion"] = ["take_everything"]
+    benchmark["multiview"]["fat_scm_late_fusion"] = ["take_everything"]
     return benchmark
 
 
@@ -25,7 +25,7 @@ def getArgs(args, benchmark, views, viewsIndices, randomState, directory, result
         monoviewDecisions = np.array([genMulticlassMonoviewDecision(monoviewResult, classificationIndices) for monoviewResult in resultsMonoview])
     monoviewDecisions = np.transpose(monoviewDecisions)
     #monoviewDecisions = np.transpose(np.array([monoviewResult[1][3] for monoviewResult in resultsMonoview]))
-    arguments = {"CL_type": "FatSCMLateFusion",
+    arguments = {"CL_type": "fat_scm_late_fusion",
                  "views": ["all"],
                  "NB_VIEW": len(resultsMonoview),
                  "viewsIndices": range(len(resultsMonoview)),
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/FatSCMLateFusion/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/__init__.py
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/analyzeResults.py
new file mode 100644
index 0000000000000000000000000000000000000000..7773f1dcec38f4aba808ec6fc8bd8aa806af1230
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fat_scm_late_fusion/analyzeResults.py
@@ -0,0 +1,21 @@
+from ...multiview import analyzeResults
+
+# Author-Info
+__author__ = "Baptiste Bauvin"
+__status__ = "Prototype"  # Production, Development, Prototype
+
+
+def execute(classifier, trainLabels,
+            testLabels, DATASET,
+            classificationKWARGS, classificationIndices,
+            LABELS_DICTIONARY, views, nbCores, times,
+            name, KFolds,
+            hyperParamSearch, nIter, metrics,
+            viewsIndices, randomState, labels, classifierModule):
+    return analyzeResults.execute(classifier, trainLabels,
+            testLabels, DATASET,
+            classificationKWARGS, classificationIndices,
+            LABELS_DICTIONARY, views, nbCores, times,
+            name, KFolds,
+            hyperParamSearch, nIter, metrics,
+            viewsIndices, randomState, labels, classifierModule)
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/FusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/FusionModule.py
similarity index 82%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/FusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/FusionModule.py
index 975403008fa0511787c345759fdd01076062c89f..991a33639963fe2182b42adc2c240ae92ce94e15 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/FusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/FusionModule.py
@@ -10,8 +10,8 @@ try:
 except ValueError:
     import pdb;pdb.set_trace()
 
-from ... import MonoviewClassifiers
-from ...utils.Dataset import getV
+from ... import monoview_classifiers
+from ...utils.dataset import getV
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -23,70 +23,70 @@ def genName(config):
         classifierRedNames = [classifierName[:4] for classifierName in config["classifiersNames"]]
         return "Late-" + str(config["fusionMethod"][:4])#+"-"+"-".join(classifierRedNames)
     elif config["fusionType"] == "EarlyFusion":
-        monoview_short_name = getattr(getattr(MonoviewClassifiers, config["classifiersNames"]),
-                                         config["classifiersNames"])().get_name_for_fusion()
+        monoview_short_name = getattr(getattr(monoview_classifiers, config["classifiersNames"]),
+                                      config["classifiersNames"])().get_name_for_fusion()
         return "Early-" + config["fusionMethod"][:4] + "-" + monoview_short_name
 
 
 def getBenchmark(benchmark, args=None):
     """Used to generate the list of fusion classifiers for the benchmark"""
     fusionModulesNames = [name for _, name, isPackage
-                          in pkgutil.iter_modules(['./MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods']) if not isPackage]
+                          in pkgutil.iter_modules(['./mono_multi_view_classifiers/multiview_classifiers/fusion/Methods']) if not isPackage]
     fusionMethods = dict((fusionModulesName, [name for _, name, isPackage in
                                               pkgutil.iter_modules(
-                                                  ["./MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/" + fusionModulesName + "Package"])
+                                                  ["./mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/" + fusionModulesName + "Package"])
                                               if not isPackage])
                          for fusionModulesName in fusionModulesNames)
     if args is None:
         allMonoviewAlgos = [name for _, name, isPackage in
-                            pkgutil.iter_modules(['./MonoMultiViewClassifiers/MonoviewClassifiers'])
+                            pkgutil.iter_modules(['./mono_multi_view_classifiers/monoview_classifiers'])
                             if (not isPackage)]
         fusionMonoviewClassifiers = allMonoviewAlgos
         allFusionAlgos = {"Methods": fusionMethods, "Classifiers": fusionMonoviewClassifiers}
-        benchmark["Multiview"]["Fusion"] = allFusionAlgos
+        benchmark["multiview"]["fusion"] = allFusionAlgos
     else:
-        benchmark["Multiview"]["Fusion"] = {}
+        benchmark["multiview"]["fusion"] = {}
         if args.FU_types != [""]:
-            benchmark["Multiview"]["Fusion"]["Methods"] = dict(
+            benchmark["multiview"]["fusion"]["Methods"] = dict(
                 (fusionType, []) for fusionType in args.FU_types)
         else:
-            benchmark["Multiview"]["Fusion"]["Methods"] = dict(
+            benchmark["multiview"]["fusion"]["Methods"] = dict(
                 (fusionModulesName, "_") for fusionModulesName in fusionModulesNames)
-        if "LateFusion" in benchmark["Multiview"]["Fusion"]["Methods"]:
+        if "LateFusion" in benchmark["multiview"]["fusion"]["Methods"]:
             if args.FU_late_methods == [""]:
-                benchmark["Multiview"]["Fusion"]["Methods"]["LateFusion"] = [name for _, name, isPackage in
+                benchmark["multiview"]["fusion"]["Methods"]["LateFusion"] = [name for _, name, isPackage in
                                                                              pkgutil.iter_modules([
-                                                                                 "./MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage"])
+                                                                                 "./mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage"])
                                                                              if not isPackage]
             else:
-                benchmark["Multiview"]["Fusion"]["Methods"]["LateFusion"] = args.FU_late_methods
-        if "EarlyFusion" in benchmark["Multiview"]["Fusion"]["Methods"]:
+                benchmark["multiview"]["fusion"]["Methods"]["LateFusion"] = args.FU_late_methods
+        if "EarlyFusion" in benchmark["multiview"]["fusion"]["Methods"]:
             if args.FU_early_methods == [""]:
-                benchmark["Multiview"]["Fusion"]["Methods"]["EarlyFusion"] = [name for _, name, isPackage in
+                benchmark["multiview"]["fusion"]["Methods"]["EarlyFusion"] = [name for _, name, isPackage in
                                                                               pkgutil.iter_modules([
-                                                                                  "./MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusionPackage"])
+                                                                                  "./mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusionPackage"])
                                                                               if not isPackage]
             else:
-                benchmark["Multiview"]["Fusion"]["Methods"]["EarlyFusion"] = args.FU_early_methods
+                benchmark["multiview"]["fusion"]["Methods"]["EarlyFusion"] = args.FU_early_methods
         if args.CL_algos_monoview == ['']:
-            benchmark["Multiview"]["Fusion"]["Classifiers"] = [name for _, name, isPackage in
-                                                               pkgutil.iter_modules(['./MonoMultiViewClassifiers/MonoviewClassifiers'])
+            benchmark["multiview"]["fusion"]["Classifiers"] = [name for _, name, isPackage in
+                                                               pkgutil.iter_modules(['./mono_multi_view_classifiers/monoview_classifiers'])
                                                                if (not isPackage) and (name != "SGD") and (
                                                                    name[:3] != "SVM")
                                                                and (name != "SCM")]
         else:
-            benchmark["Multiview"]["Fusion"]["Classifiers"] = args.CL_algos_monoview
+            benchmark["multiview"]["fusion"]["Classifiers"] = args.CL_algos_monoview
     return benchmark
 
 
 def getArgs(args, benchmark, views, viewsIndices, randomState, directory, resultsMonoview, classificationIndices):
     """Used to generate the list of arguments for each fusion experimentation"""
-    if not "Monoview" in benchmark and not args.FU_L_select_monoview in ["randomClf", "Determined"]:
+    if not "monoview" in benchmark and not args.FU_L_select_monoview in ["randomClf", "Determined"]:
         args.FU_L_select_monoview = "randomClf"
     argumentsList = []
-    for fusionType in benchmark["Multiview"]["Fusion"]["Methods"]:
+    for fusionType in benchmark["multiview"]["fusion"]["Methods"]:
         fusionTypePackage = getattr(Methods, fusionType + "Package")
-        for fusionMethod in benchmark["Multiview"]["Fusion"]["Methods"][fusionType]:
+        for fusionMethod in benchmark["multiview"]["fusion"]["Methods"][fusionType]:
             fusionMethodModule = getattr(fusionTypePackage, fusionMethod)
             arguments = fusionMethodModule.getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview,
                                                    classificationIndices)
@@ -131,7 +131,7 @@ def genParamsSets(classificationKWARGS, randomState, nIter=1):
 #     bestSettings = []
 #     for classifierIndex, classifierName in enumerate(classifiersNames):
 #         logging.debug("\tStart:\t Random search for " + classifierName + " with " + str(nIter) + " iterations")
-#         classifierModule = getattr(MonoviewClassifiers, classifierName)
+#         classifierModule = getattr(monoview_classifiers, classifierName)
 #         classifierMethod = getattr(classifierModule, "hyperParamSearch")
 #         if fusionTypeName == "LateFusion":
 #             bestSettings.append(classifierMethod(getV(DATASET, viewsIndices[classifierIndex], learningIndices),
@@ -153,7 +153,7 @@ def genParamsSets(classificationKWARGS, randomState, nIter=1):
 
 
 class FusionClass:
-    """The global representant of Fusion"""
+    """The global representant of fusion"""
     def __init__(self, randomState, NB_CORES=1, **kwargs):
         fusionType = kwargs['fusionType']
         fusionMethod = kwargs['fusionMethod']
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusion.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusion.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusion.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusion.py
index 0199062d8d6b9a6ab31571dea40e773680458f1d..07a63a6f8e6380c6ff463a0359cd73a63625a34b 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusion.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusion.py
@@ -2,8 +2,8 @@
 # -*- encoding: utf-8
 
 import numpy as np
-from ....utils.Dataset import getV
-from .... import MonoviewClassifiers
+from ....utils.dataset import getV
+from .... import monoview_classifiers
 
 class EarlyFusionClassifier(object):
     def __init__(self, randomState, monoviewClassifierName, monoviewClassifierConfig, NB_CORES=1):
@@ -16,7 +16,7 @@ class EarlyFusionClassifier(object):
             monoviewClassifierConfig = dict((str(configIndex), config[0]) for configIndex, config in
                                             enumerate(monoviewClassifierConfig
                                                       ))
-        monoviewClassifierModule = getattr(MonoviewClassifiers, self.monoviewClassifierName)
+        monoviewClassifierModule = getattr(monoview_classifiers, self.monoviewClassifierName)
         if monoviewClassifierConfig is not None:
             self.monoviewClassifier = getattr(monoviewClassifierModule, self.monoviewClassifierName)(
                 random_state=randomState, **monoviewClassifierConfig)
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusionPackage/WeightedLinear.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusionPackage/WeightedLinear.py
similarity index 91%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusionPackage/WeightedLinear.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusionPackage/WeightedLinear.py
index c0dd0bfc47b066eae131a96bea30cd5cc3dd77cc..79059d5ca203ccc3a2a5fcc651086431262403cb 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusionPackage/WeightedLinear.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusionPackage/WeightedLinear.py
@@ -1,13 +1,13 @@
 import numpy as np
 
 from ...Methods.EarlyFusion import EarlyFusionClassifier
-from ..... import MonoviewClassifiers
+from ..... import monoview_classifiers
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
     nbView = classificationKWARGS["nbView"]
     if classificationKWARGS["classifiersConfigs"] is None:
-        monoviewClassifierModule = getattr(MonoviewClassifiers, classificationKWARGS["classifiersNames"])
+        monoviewClassifierModule = getattr(monoview_classifiers, classificationKWARGS["classifiersNames"])
         paramsMonoview = monoviewClassifierModule.paramsToSet(nIter, randomState)
     paramsSets = []
     for iterIndex in range(nIter):
@@ -22,13 +22,13 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
     if args.FU_E_cl_names != ['']:
         pass
     else:
-        monoviewClassifierModulesNames = benchmark["Monoview"]
+        monoviewClassifierModulesNames = benchmark["monoview"]
         args.FU_E_cl_names = monoviewClassifierModulesNames
         args.FU_E_cl_config = [None for _ in monoviewClassifierModulesNames]
     for classifierName, classifierConfig in zip(args.FU_E_cl_names, args.FU_E_cl_config):
-        monoviewClassifierModule = getattr(MonoviewClassifiers, classifierName)
+        monoviewClassifierModule = getattr(monoview_classifiers, classifierName)
         if classifierConfig is not None:
-            arguments = {"CL_type": "Fusion",
+            arguments = {"CL_type": "fusion",
                          "views": views,
                          "NB_VIEW": len(views),
                          "viewsIndices": viewsIndices,
@@ -44,7 +44,7 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
                                           'fusionMethodConfig': args.FU_E_method_configs,
                                           "nbView": (len(viewsIndices))}}
         else:
-            arguments = {"CL_type": "Fusion",
+            arguments = {"CL_type": "fusion",
                          "views": views,
                          "NB_VIEW": len(views),
                          "viewsIndices": viewsIndices,
@@ -81,7 +81,7 @@ class WeightedLinear(EarlyFusionClassifier):
             trainIndices = range(DATASET.get("Metadata").attrs["datasetLength"])
         self.weights /= float(max(self.weights))
         self.makeMonoviewData_hdf5(DATASET, weights=self.weights, usedIndices=trainIndices, viewsIndices=viewsIndices)
-        # monoviewClassifierModule = getattr(MonoviewClassifiers, self.monoviewClassifierName)
+        # monoviewClassifierModule = getattr(monoview_classifiers, self.monoviewClassifierName)
         self.monoviewClassifier.fit(self.monoviewData, labels[trainIndices])
                                                                # self.randomState,
                                                                # NB_CORES=self.nbCores,
@@ -112,7 +112,7 @@ 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)
+        # monoviewClassifierModule = getattr(monoview_classifiers, monoviewClassifiersNames)
         configString += self.monoviewClassifier.getConfig()
         return configString
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusionPackage/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusionPackage/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/EarlyFusionPackage/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/EarlyFusionPackage/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusion.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusion.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusion.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusion.py
index 90807af20ff9c324ddf157ffeee38635a5ce94eb..8beb6a299404e32d8b1791da34cad45961f87668 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusion.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusion.py
@@ -7,9 +7,9 @@ from joblib import Parallel, delayed
 import sys
 import math
 
-from .... import MonoviewClassifiers
-from .... import Metrics
-from ....utils.Dataset import getV
+from .... import monoview_classifiers
+from .... import metrics
+from ....utils.dataset import getV
 
 
 # def canProbasClassifier(classifierConfig):
@@ -23,7 +23,7 @@ from ....utils.Dataset import getV
 def fitMonoviewClassifier(monoviewClassifier, data, labels, needProbas, randomState, nbCores=1):
         if needProbas and not monoviewClassifier.canProbas():
             DTConfig = {"max_depth": 300, "criterion": "entropy", "splitter": "random"}
-            monoviewClassifier = getattr(MonoviewClassifiers, "DecisionTree")(random_state=randomState, **DTConfig)
+            monoviewClassifier = getattr(monoview_classifiers, "DecisionTree")(random_state=randomState, **DTConfig)
             classifier = monoviewClassifier.fit(data, labels)
             return classifier
         else:
@@ -77,7 +77,7 @@ def bestScore(allClassifersNames, directory, viewsIndices, resultsMonoview, clas
     scores = np.zeros((nbViews, nbClassifiers))
     classifiersNames = [[] for _ in viewsIndices]
     metricName = resultsMonoview[0].metrics_scores.keys()[0]
-    metricModule = getattr(Metrics, metricName)
+    metricModule = getattr(metrics, metricName)
     if metricModule.getConfig()[-14] == "h":
         betterHigh = True
     else:
@@ -117,7 +117,7 @@ class LateFusionClassifier(object):
     def __init__(self, randomState, monoviewClassifiersNames, monoviewClassifiersConfigs, monoviewSelection,
                  NB_CORES=1):
         self.monoviewClassifiersNames = monoviewClassifiersNames
-        monoviewClassifiersModules = [getattr(MonoviewClassifiers, classifierName)
+        monoviewClassifiersModules = [getattr(monoview_classifiers, classifierName)
                                       for classifierName in self.monoviewClassifiersNames]
         if type(monoviewClassifiersConfigs[0]) == dict:
             self.monoviewClassifiers = [
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/BayesianInference.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/BayesianInference.py
similarity index 91%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/BayesianInference.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/BayesianInference.py
index d825f24a9ec951460314292d4d5a9afd6e422d57..2f6d9b723fedf68094fe591b37b638fe81f729f5 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/BayesianInference.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/BayesianInference.py
@@ -2,8 +2,8 @@ import numpy as np
 from sklearn.metrics import accuracy_score
 import pkgutil
 
-from .....utils.Dataset import getV
-from ..... import MonoviewClassifiers
+from .....utils.dataset import getV
+from ..... import monoview_classifiers
 from ..LateFusion import LateFusionClassifier, getClassifiers, getConfig
 
 
@@ -21,14 +21,14 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
     if args.FU_L_cl_names != ['']:
         args.FU_L_select_monoview = "user_defined"
     else:
-        monoviewClassifierModulesNames = benchmark["Monoview"]
+        monoviewClassifierModulesNames = benchmark["monoview"]
         args.FU_L_cl_names = getClassifiers(args.FU_L_select_monoview, monoviewClassifierModulesNames, directory,
                                             viewsIndices, resultsMonoview, classificationIndices)
-    monoviewClassifierModules = [getattr(MonoviewClassifiers, classifierName)
+    monoviewClassifierModules = [getattr(monoview_classifiers, classifierName)
                                  for classifierName in args.FU_L_cl_names]
-    if args.FU_L_cl_names == [""] and args.CL_type == ["Multiview"]:
-        raise AttributeError("You must perform Monoview classification or specify "
-                             "which monoview classifier to use Late Fusion")
+    if args.FU_L_cl_names == [""] and args.CL_type == ["multiview"]:
+        raise AttributeError("You must perform monoview classification or specify "
+                             "which monoview classifier to use Late fusion")
     if args.FU_L_cl_config != ['']:
         classifiersConfigs = [
             monoviewClassifierModule.getKWARGS([arg.split(":") for arg in classifierConfig.split(",")])
@@ -36,7 +36,7 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
             in zip(monoviewClassifierModules, args.FU_L_cl_config)]
     else:
         classifiersConfigs = getConfig(args.FU_L_cl_names, resultsMonoview, viewsIndices)
-    arguments = {"CL_type": "Fusion",
+    arguments = {"CL_type": "fusion",
                  "views": views,
                  "NB_VIEW": len(views),
                  "viewsIndices": viewsIndices,
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/MajorityVoting.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/MajorityVoting.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/MajorityVoting.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/MajorityVoting.py
index 34086cc82ff5745b8720c1a6872bac68818dfca3..bef30f9cd687e389745a8b1f117718b84faeb2d4 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/MajorityVoting.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/MajorityVoting.py
@@ -2,9 +2,9 @@ import numpy as np
 # from sklearn.metrics import accuracy_score
 # import pkgutil
 
-from .....utils.Dataset import getV
+from .....utils.dataset import getV
 from ..LateFusion import LateFusionClassifier, getClassifiers, getConfig
-from ..... import MonoviewClassifiers
+from ..... import monoview_classifiers
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
@@ -21,14 +21,14 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
     if args.FU_L_cl_names != ['']:
         pass
     else:
-        monoviewClassifierModulesNames = benchmark["Monoview"]
+        monoviewClassifierModulesNames = benchmark["monoview"]
         args.FU_L_cl_names = getClassifiers(args.FU_L_select_monoview, monoviewClassifierModulesNames, directory,
                                             viewsIndices, resultsMonoview, classificationIndices)
-    monoviewClassifierModules = [getattr(MonoviewClassifiers, classifierName)
+    monoviewClassifierModules = [getattr(monoview_classifiers, classifierName)
                                  for classifierName in args.FU_L_cl_names]
-    if args.FU_L_cl_names == [""] and args.CL_type == ["Multiview"]:
-        raise AttributeError("You must perform Monoview classification or specify "
-                             "which monoview classifier to use Late Fusion")
+    if args.FU_L_cl_names == [""] and args.CL_type == ["multiview"]:
+        raise AttributeError("You must perform monoview classification or specify "
+                             "which monoview classifier to use Late fusion")
     if args.FU_L_cl_config != ['']:
         classifiersConfigs = [
             monoviewClassifierModule.getKWARGS([arg.split(":") for arg in classifierConfig.split(",")])
@@ -36,7 +36,7 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
             in zip(monoviewClassifierModules, args.FU_L_cl_config)]
     else:
         classifiersConfigs = getConfig(args.FU_L_cl_names, resultsMonoview, viewsIndices)
-    arguments = {"CL_type": "Fusion",
+    arguments = {"CL_type": "fusion",
                  "views": views,
                  "NB_VIEW": len(views),
                  "viewsIndices": viewsIndices,
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/SCMForLinear.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/SCMForLinear.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/SCMForLinear.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/SCMForLinear.py
index 705c6a8feb89c4d57104deeb34128d6893156646..c5e7b9acab1504a506751722ebfbd13aa8637a9f 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/SCMForLinear.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/SCMForLinear.py
@@ -8,8 +8,8 @@ from sklearn.metrics import accuracy_score
 import itertools
 
 from ..LateFusion import LateFusionClassifier, getClassifiers, getConfig
-from ..... import MonoviewClassifiers
-from .....utils.Dataset import getV
+from ..... import monoview_classifiers
+from .....utils.dataset import getV
 
 
 class DecisionStumpSCMNew(BaseEstimator, ClassifierMixin):
@@ -59,14 +59,14 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
     if args.FU_L_cl_names != ['']:
         pass
     else:
-        monoviewClassifierModulesNames = benchmark["Monoview"]
+        monoviewClassifierModulesNames = benchmark["monoview"]
         args.FU_L_cl_names = getClassifiers(args.FU_L_select_monoview, monoviewClassifierModulesNames, directory,
                                             viewsIndices, resultsMonoview, classificationIndices)
-    monoviewClassifierModules = [getattr(MonoviewClassifiers, classifierName)
+    monoviewClassifierModules = [getattr(monoview_classifiers, classifierName)
                                  for classifierName in args.FU_L_cl_names]
-    if args.FU_L_cl_names == [""] and args.CL_type == ["Multiview"]:
-        raise AttributeError("You must perform Monoview classification or specify "
-                             "which monoview classifier to use Late Fusion")
+    if args.FU_L_cl_names == [""] and args.CL_type == ["multiview"]:
+        raise AttributeError("You must perform monoview classification or specify "
+                             "which monoview classifier to use Late fusion")
     if args.FU_L_cl_config != ['']:
         classifiersConfigs = [
             monoviewClassifierModule.getKWARGS([arg.split(":") for arg in classifierConfig.split(",")])
@@ -74,7 +74,7 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
             in zip(monoviewClassifierModules, args.FU_L_cl_config)]
     else:
         classifiersConfigs = getConfig(args.FU_L_cl_names, resultsMonoview, viewsIndices)
-    arguments = {"CL_type": "Fusion",
+    arguments = {"CL_type": "fusion",
                  "views": views,
                  "NB_VIEW": len(views),
                  "viewsIndices": viewsIndices,
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/SVMForLinear.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/SVMForLinear.py
similarity index 92%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/SVMForLinear.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/SVMForLinear.py
index 260cef5790d659a58707346ba11be92fae363738..8b4c984039282d8aa49e91a6328663f0a48768e8 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/SVMForLinear.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/SVMForLinear.py
@@ -4,8 +4,8 @@ from sklearn.svm import SVC
 import pkgutil
 
 from ..LateFusion import LateFusionClassifier, getClassifiers, getConfig
-from .....utils.Dataset import getV
-from ..... import MonoviewClassifiers
+from .....utils.dataset import getV
+from ..... import monoview_classifiers
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
@@ -19,14 +19,14 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
     if args.FU_L_cl_names != ['']:
         pass
     else:
-        monoviewClassifierModulesNames = benchmark["Monoview"]
+        monoviewClassifierModulesNames = benchmark["monoview"]
         args.FU_L_cl_names = getClassifiers(args.FU_L_select_monoview, monoviewClassifierModulesNames, directory,
                                             viewsIndices, resultsMonoview, classificationIndices)
-    monoviewClassifierModules = [getattr(MonoviewClassifiers, classifierName)
+    monoviewClassifierModules = [getattr(monoview_classifiers, classifierName)
                                  for classifierName in args.FU_L_cl_names]
-    if args.FU_L_cl_names == [""] and args.CL_type == ["Multiview"]:
-        raise AttributeError("You must perform Monoview classification or specify "
-                             "which monoview classifier to use Late Fusion")
+    if args.FU_L_cl_names == [""] and args.CL_type == ["multiview"]:
+        raise AttributeError("You must perform monoview classification or specify "
+                             "which monoview classifier to use Late fusion")
     if args.FU_L_cl_config != ['']:
         classifiersConfigs = [
             monoviewClassifierModule.getKWARGS([arg.split(":") for arg in classifierConfig.split(",")])
@@ -34,7 +34,7 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
             in zip(monoviewClassifierModules, args.FU_L_cl_config)]
     else:
         classifiersConfigs = getConfig(args.FU_L_cl_names, resultsMonoview, viewsIndices)
-    arguments = {"CL_type": "Fusion",
+    arguments = {"CL_type": "fusion",
                  "views": views,
                  "NB_VIEW": len(views),
                  "viewsIndices": viewsIndices,
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/WeightedLinear.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/WeightedLinear.py
similarity index 91%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/WeightedLinear.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/WeightedLinear.py
index ad5b2fadd46d73a6cda3d4462e38bf4a603ad0c9..d7d9f418bdaeccf190e9534e2ea407b71fdc1eef 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/WeightedLinear.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/WeightedLinear.py
@@ -2,9 +2,9 @@ import numpy as np
 from sklearn.metrics import accuracy_score
 import pkgutil
 
-from ..... import MonoviewClassifiers
+from ..... import monoview_classifiers
 from ..LateFusion import LateFusionClassifier, getClassifiers, getConfig
-from .....utils.Dataset import getV
+from .....utils.dataset import getV
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
@@ -21,14 +21,14 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
     if args.FU_L_cl_names != ['']:
         pass
     else:
-        monoviewClassifierModulesNames = benchmark["Monoview"]
+        monoviewClassifierModulesNames = benchmark["monoview"]
         args.FU_L_cl_names = getClassifiers(args.FU_L_select_monoview, monoviewClassifierModulesNames, directory,
                                             viewsIndices, resultsMonoview, classificationIndices)
-    monoviewClassifierModules = [getattr(MonoviewClassifiers, classifierName)
+    monoviewClassifierModules = [getattr(monoview_classifiers, classifierName)
                                  for classifierName in args.FU_L_cl_names]
-    if args.FU_L_cl_names == [""] and args.CL_type == ["Multiview"]:
-        raise AttributeError("You must perform Monoview classification or specify "
-                             "which monoview classifier to use Late Fusion")
+    if args.FU_L_cl_names == [""] and args.CL_type == ["multiview"]:
+        raise AttributeError("You must perform monoview classification or specify "
+                             "which monoview classifier to use Late fusion")
     if args.FU_L_cl_config != ['']:
         classifiersConfigs = [
             monoviewClassifierModule.getKWARGS([arg.split(":") for arg in classifierConfig.split(",")])
@@ -36,7 +36,7 @@ def getArgs(benchmark, args, views, viewsIndices, directory, resultsMonoview, cl
             in zip(monoviewClassifierModules, args.FU_L_cl_config)]
     else:
         classifiersConfigs = getConfig(args.FU_L_cl_names, resultsMonoview, viewsIndices)
-    arguments = {"CL_type": "Fusion",
+    arguments = {"CL_type": "fusion",
                  "views": views,
                  "NB_VIEW": len(views),
                  "viewsIndices": viewsIndices,
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/LateFusionPackage/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/LateFusionPackage/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/Methods/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/Methods/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/__init__.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/analyzeResults.py
similarity index 95%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/analyzeResults.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/analyzeResults.py
index 0348bdd827c715e998644c83cabc9cbe6f319f41..d7ba82d2382483982fc174401ae6d9f51e19f301 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/analyzeResults.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/fusion/analyzeResults.py
@@ -1,4 +1,4 @@
-from ...Multiview import analyzeResults
+from ...multiview import analyzeResults
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/PseudoCQFusionModule.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/PseudoCQFusionModule.py
similarity index 75%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/PseudoCQFusionModule.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/PseudoCQFusionModule.py
index 05b1bb381abf0486ba2b8aaf3321343230e48d63..fa26a47e736cdcace540f1befbc7358a875ad0e3 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/PseudoCQFusionModule.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/PseudoCQFusionModule.py
@@ -1,14 +1,14 @@
-from ...Multiview.Additions import diversity_utils
-from ..DifficultyFusion.DifficultyFusionModule import difficulty
-from ..DoubleFaultFusion.DoubleFaultFusionModule import doubleFault
+from ...multiview.Additions import diversity_utils
+from ..difficulty_fusion.difficulty_fusion import difficulty
+from ..double_fault_fusion.DoubleFaultFusionModule import doubleFault
 
 
 def genName(config):
-    return "PseudoCQFusion"
+    return "pseudo_cq_fusion"
 
 
 def getBenchmark(benchmark, args=None):
-    benchmark["Multiview"]["PseudoCQFusion"] = ["take_everything"]
+    benchmark["multiview"]["pseudo_cq_fusion"] = ["take_everything"]
     return benchmark
 
 
@@ -20,7 +20,7 @@ def getArgs(args, benchmark, views, viewsIndices, randomState, directory, result
     return diversity_utils.getArgs(args, benchmark, views,
                                    viewsIndices, randomState, directory,
                                    resultsMonoview, classificationIndices,
-                                   [doubleFault, difficulty], "PseudoCQFusion")
+                                   [doubleFault, difficulty], "pseudo_cq_fusion")
 
 
 def genParamsSets(classificationKWARGS, randomState, nIter=1):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/__init__.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/__init__.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/MultiviewClassifiers/PseudoCQFusion/__init__.py
rename to multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/__init__.py
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/analyzeResults.py b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/analyzeResults.py
new file mode 100644
index 0000000000000000000000000000000000000000..7773f1dcec38f4aba808ec6fc8bd8aa806af1230
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/analyzeResults.py
@@ -0,0 +1,21 @@
+from ...multiview import analyzeResults
+
+# Author-Info
+__author__ = "Baptiste Bauvin"
+__status__ = "Prototype"  # Production, Development, Prototype
+
+
+def execute(classifier, trainLabels,
+            testLabels, DATASET,
+            classificationKWARGS, classificationIndices,
+            LABELS_DICTIONARY, views, nbCores, times,
+            name, KFolds,
+            hyperParamSearch, nIter, metrics,
+            viewsIndices, randomState, labels, classifierModule):
+    return analyzeResults.execute(classifier, trainLabels,
+            testLabels, DATASET,
+            classificationKWARGS, classificationIndices,
+            LABELS_DICTIONARY, views, nbCores, times,
+            name, KFolds,
+            hyperParamSearch, nIter, metrics,
+            viewsIndices, randomState, labels, classifierModule)
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/ResultAnalysis.py b/multiview_platform/mono_multi_view_classifiers/result_analysis.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/ResultAnalysis.py
rename to multiview_platform/mono_multi_view_classifiers/result_analysis.py
index df79a60e94154361c95bfb8ab09841ca02fe98bc..59ed1d8ed9e3583aef28fc0541fafef296a8982b 100644
--- a/multiview_platform/MonoMultiViewClassifiers/ResultAnalysis.py
+++ b/multiview_platform/mono_multi_view_classifiers/result_analysis.py
@@ -12,7 +12,7 @@ import numpy as np
 import pandas as pd
 
 # Import own Modules
-from . import Metrics
+from . import metrics
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -615,7 +615,7 @@ def genMetricsScoresMulticlass(results, trueLabels, metrics,
     logging.debug("Start:\t Getting multiclass scores for each metric")
 
     for metric in metrics:
-        metricModule = getattr(Metrics, metric[0])
+        metricModule = getattr(metrics, metric[0])
         for iterIndex, iterResults in enumerate(results):
 
             for argumentsDictionary in argumentsDictionaries:
diff --git a/multiview_platform/mono_multi_view_classifiers/utils/__init__.py b/multiview_platform/mono_multi_view_classifiers/utils/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e0473b520b385389e967e567261bdb95a360aa37
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/utils/__init__.py
@@ -0,0 +1 @@
+from . import dataset, execution, hyper_parameter_search, transformations
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/Dataset.py b/multiview_platform/mono_multi_view_classifiers/utils/dataset.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/utils/Dataset.py
rename to multiview_platform/mono_multi_view_classifiers/utils/dataset.py
index 71ff205b3cd176ef6256da9910db007344cc13d9..6a19674c653148ab554121ba41f8f31c66cf9904 100644
--- a/multiview_platform/MonoMultiViewClassifiers/utils/Dataset.py
+++ b/multiview_platform/mono_multi_view_classifiers/utils/dataset.py
@@ -7,7 +7,7 @@ import h5py
 import numpy as np
 from scipy import sparse
 
-from . import GetMultiviewDb as DB
+from . import get_multiview_db as DB
 
 
 def getV(DATASET, viewIndex, usedIndices=None):
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/execution.py b/multiview_platform/mono_multi_view_classifiers/utils/execution.py
similarity index 98%
rename from multiview_platform/MonoMultiViewClassifiers/utils/execution.py
rename to multiview_platform/mono_multi_view_classifiers/utils/execution.py
index dc8507bbc4f305c693d4bd213811aa9058927002..2bd4770024c7fdd955de927d5623c5046fb0860b 100644
--- a/multiview_platform/MonoMultiViewClassifiers/utils/execution.py
+++ b/multiview_platform/mono_multi_view_classifiers/utils/execution.py
@@ -7,7 +7,7 @@ import time
 import numpy as np
 import sklearn
 
-from . import GetMultiviewDb as DB
+from . import get_multiview_db as DB
 
 
 def parseTheArgs(arguments):
@@ -70,7 +70,7 @@ def parseTheArgs(arguments):
                                type=float, default=[0.0])
     groupStandard.add_argument('--res_dir', metavar='STRING', action='store',
                                help='The path to the result directory',
-                               default="../Results/")
+                               default="../results/")
 
     groupClass = parser.add_argument_group('Classification arguments')
     groupClass.add_argument('--CL_multiclassMethod', metavar='STRING',
@@ -97,9 +97,9 @@ def parseTheArgs(arguments):
                                  'selected', default=["yes", "no"])
     groupClass.add_argument('--CL_type', metavar='STRING', action='store',
                             nargs="+",
-                            help='Determine whether to use Multiview and/or '
-                                 'Monoview, or Benchmark classification',
-                            default=['Monoview', 'Multiview'])
+                            help='Determine whether to use multiview and/or '
+                                 'monoview, or Benchmark classification',
+                            default=['monoview', 'multiview'])
     groupClass.add_argument('--CL_algos_monoview', metavar='STRING',
                             action='store', nargs="+",
                             help='Determine which monoview classifier to use '
@@ -589,7 +589,7 @@ def parseTheArgs(arguments):
                                   default=[1e-08])
 
 #
-# Multiview args
+# multiview args
 #
 
     groupMumbo = parser.add_argument_group('Mumbo arguments')
@@ -609,12 +609,12 @@ def parseTheArgs(arguments):
                             help='Try all the monoview classifiers combinations for each view',
                             default=False)
 
-    groupFusion = parser.add_argument_group('Fusion arguments')
+    groupFusion = parser.add_argument_group('fusion arguments')
     groupFusion.add_argument('--FU_types', metavar='STRING', action='store',
                              nargs="+",
                              help='Determine which type of fusion to use',
                              default=[''])
-    groupEarlyFusion = parser.add_argument_group('Early Fusion arguments')
+    groupEarlyFusion = parser.add_argument_group('Early fusion arguments')
     groupEarlyFusion.add_argument('--FU_early_methods', metavar='STRING',
                                   action='store', nargs="+",
                                   help='Determine which early fusion method of fusion to use',
@@ -634,7 +634,7 @@ def parseTheArgs(arguments):
                                   help='Name of the classifiers used for each early fusion method',
                                   default=[''])
 
-    groupLateFusion = parser.add_argument_group('Late Fusion arguments')
+    groupLateFusion = parser.add_argument_group('Late fusion arguments')
     groupLateFusion.add_argument('--FU_late_methods', metavar='STRING',
                                  action='store', nargs="+",
                                  help='Determine which late fusion method of fusion to use',
@@ -656,7 +656,7 @@ def parseTheArgs(arguments):
                                  help='Determine which method to use to select the monoview classifiers',
                                  default="intersect")
 
-    groupFatLateFusion = parser.add_argument_group('Fat Late Fusion arguments')
+    groupFatLateFusion = parser.add_argument_group('Fat Late fusion arguments')
     groupFatLateFusion.add_argument('--FLF_weights', metavar='FLOAT',
                                     action='store', nargs="+",
                                     help='Determine the weights of each monoview decision for FLF',
@@ -664,7 +664,7 @@ def parseTheArgs(arguments):
                                     default=[])
 
     groupFatSCMLateFusion = parser.add_argument_group(
-        'Fat SCM Late Fusion arguments')
+        'Fat SCM Late fusion arguments')
     groupFatSCMLateFusion.add_argument('--FSCMLF_p', metavar='FLOAT',
                                        action='store',
                                        help='Determine the p argument of the SCM',
@@ -1005,7 +1005,7 @@ def genArgumentDictionaries(labelsDictionary, directories, multiclassLabels,
     statsIterRandomStates : list of numpy.random.RandomState objects
         Multiple random states, one for each sattistical iteration of the same benchmark.
     metrics : list of lists
-        Metrics that will be used to evaluate the algorithms performance.
+        metrics that will be used to evaluate the algorithms performance.
     argumentDictionaries : dictionary
         Dictionary resuming all the specific arguments for the benchmark, oe dictionary for each classifier.
     benchmark : dictionary
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/GetMultiviewDb.py b/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/utils/GetMultiviewDb.py
rename to multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/HyperParameterSearch.py b/multiview_platform/mono_multi_view_classifiers/utils/hyper_parameter_search.py
similarity index 99%
rename from multiview_platform/MonoMultiViewClassifiers/utils/HyperParameterSearch.py
rename to multiview_platform/mono_multi_view_classifiers/utils/hyper_parameter_search.py
index 08b23063f2e1e58a9b536c371b56dc73698e7353..7124c2654125c1b454f5a0ecec05a0277533f833 100644
--- a/multiview_platform/MonoMultiViewClassifiers/utils/HyperParameterSearch.py
+++ b/multiview_platform/mono_multi_view_classifiers/utils/hyper_parameter_search.py
@@ -4,7 +4,7 @@ import sys
 import matplotlib.pyplot as plt
 import numpy as np
 
-from .. import Metrics
+from .. import metrics
 
 
 def searchBestSettings(dataset, labels, classifierPackage, classifierName,
@@ -39,7 +39,7 @@ def randomizedSearch(dataset, labels, classifierPackage, classifierName,
     if viewsIndices is None:
         viewsIndices = range(dataset.get("Metadata").attrs["nbView"])
     metric = metrics[0]
-    metricModule = getattr(Metrics, metric[0])
+    metricModule = getattr(metrics, metric[0])
     if metric[1] is not None:
         metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                             enumerate(metric[1]))
diff --git a/multiview_platform/mono_multi_view_classifiers/utils/make_file_config.py b/multiview_platform/mono_multi_view_classifiers/utils/make_file_config.py
new file mode 100644
index 0000000000000000000000000000000000000000..de258fddc484f7524ff388a5c3318e44be176a9f
--- /dev/null
+++ b/multiview_platform/mono_multi_view_classifiers/utils/make_file_config.py
@@ -0,0 +1,91 @@
+import os, sys, inspect
+from MonoviewClassifiers.Adaboost import Adaboost
+
+
+
+class ConfigurationMaker():
+    """
+
+    """
+
+    def __init__(self):
+    classifier_dict = {"0": [Adaboost,
+                             multiview_platform.MonoMultiViewClassifiers.MonoviewClassifiers.Adaboost]}
+       for key, val in  classifier_dict.items():
+
+           __import__(val[1], locals(), globals(), [], 1)
+           sig = inspect.signature(val[1]+"."+val[0]+".__init__")
+           print(sig)
+           for arg_idx, name in enumerate(sig.parameters):
+               print(arg_idx)
+               print(name)
+
+
+def make(dir='.', output=None):
+    """
+    Generate file config from classifier files
+    :param  dir: (default'.'
+    :dir type: str or list of str
+    :return:
+    """
+
+    currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
+    parentdir = os.path.dirname(currentdir)
+    sys.path.insert(0, parentdir)
+
+    import mymodule
+     calling_module = inspect.getmodule(stack_frame[0])
+
+
+
+
+import os
+
+path = os.getcwd() + '/multiview_platform/'
+files = []
+# r=root, d=directories, f = files
+for r, d, f in os.walk(path):
+    print('dir', d)
+    print('root', r)
+    for file in f:
+        if '.py' in file and not file.startswith('__init__'):
+            print("file", file)
+            files.append(os.path.join(r, file))
+
+for f in files:
+    print(f)
+
+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(), [], 1)
+
+import glob
+
+path = 'c:\\projects\\hc2\\'
+
+files = [f for f in glob.glob(path + "**/*.txt", recursive=True)]
+
+for f in files:
+    print(f)
+
+import inspect
+
+
+# Import this to other module and call it
+def print_caller_info():
+    # Get the full stack
+    stack = inspect.stack()
+
+    # Get one level up from current
+    previous_stack_frame = stack[1]
+    print(previous_stack_frame.filename)  # Filename where caller lives
+
+    # Get the module object of the caller
+    calling_module = inspect.getmodule(stack_frame[0])
+    print(calling_module)
+    print(calling_module.__file__)
+
+
+if __name__ == '__main__':
+    print_caller_info()
\ No newline at end of file
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/Multiclass.py b/multiview_platform/mono_multi_view_classifiers/utils/multiclass.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/utils/Multiclass.py
rename to multiview_platform/mono_multi_view_classifiers/utils/multiclass.py
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/MultiviewResultAnalysis.py b/multiview_platform/mono_multi_view_classifiers/utils/multiview_result_analysis.py
similarity index 94%
rename from multiview_platform/MonoMultiViewClassifiers/utils/MultiviewResultAnalysis.py
rename to multiview_platform/mono_multi_view_classifiers/utils/multiview_result_analysis.py
index 1e8ec1c69dd311ce5b63fd7e8751a21a884f9c93..5036232294ec6abac6551bd34356f2a8de16fe0c 100644
--- a/multiview_platform/MonoMultiViewClassifiers/utils/MultiviewResultAnalysis.py
+++ b/multiview_platform/mono_multi_view_classifiers/utils/multiview_result_analysis.py
@@ -1,4 +1,4 @@
-from .. import Metrics
+from .. import metrics
 
 # Author-Info
 __author__ = "Baptiste Bauvin"
@@ -8,7 +8,7 @@ __status__ = "Prototype"  # Production, Development, Prototype
 def printMetricScore(metricScores, metrics):
     metricScoreString = "\n\n"
     for metric in metrics:
-        metricModule = getattr(Metrics, metric[0])
+        metricModule = getattr(metrics, metric[0])
         if metric[1] is not None:
             metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                                 enumerate(metric[1]))
@@ -26,7 +26,7 @@ def printMetricScore(metricScores, metrics):
 
 def getTotalMetricScores(metric, trainLabels, testLabels, validationIndices,
                          learningIndices, labels):
-    metricModule = getattr(Metrics, metric[0])
+    metricModule = getattr(metrics, metric[0])
     if metric[1] is not None:
         metricKWARGS = dict((index, metricConfig) for index, metricConfig in
                             enumerate(metric[1]))
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/Transformations.py b/multiview_platform/mono_multi_view_classifiers/utils/transformations.py
similarity index 100%
rename from multiview_platform/MonoMultiViewClassifiers/utils/Transformations.py
rename to multiview_platform/mono_multi_view_classifiers/utils/transformations.py
diff --git a/multiview_platform/Tests.py b/multiview_platform/tests.py
similarity index 71%
rename from multiview_platform/Tests.py
rename to multiview_platform/tests.py
index 25b01535d1b28e7acc5dcb78f096e02a60891fa0..90705cc440aca892f3a8bd98aad809352f1c58aa 100644
--- a/multiview_platform/Tests.py
+++ b/multiview_platform/tests.py
@@ -1,6 +1,6 @@
 # if __name__=="__main__":
 #     import unittest
-#     from .Tests.test_ExecClassif import suite
+#     from .tests.test_ExecClassif import suite
 #
 #     runner = unittest.TextTestRunner()
 #     runner.run(suite())
diff --git a/multiview_platform/Tests/Test_Metrics/__init__.py b/multiview_platform/tests/Test_Metrics/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_Metrics/__init__.py
rename to multiview_platform/tests/Test_Metrics/__init__.py
diff --git a/multiview_platform/Tests/Test_Metrics/test_accuracy_score.py b/multiview_platform/tests/Test_Metrics/test_accuracy_score.py
similarity index 100%
rename from multiview_platform/Tests/Test_Metrics/test_accuracy_score.py
rename to multiview_platform/tests/Test_Metrics/test_accuracy_score.py
diff --git a/multiview_platform/Tests/Test_MonoView/__init__.py b/multiview_platform/tests/Test_MonoView/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MonoView/__init__.py
rename to multiview_platform/tests/Test_MonoView/__init__.py
diff --git a/multiview_platform/Tests/Test_MonoView/test_ExecClassifMonoView.py b/multiview_platform/tests/Test_MonoView/test_ExecClassifMonoView.py
similarity index 80%
rename from multiview_platform/Tests/Test_MonoView/test_ExecClassifMonoView.py
rename to multiview_platform/tests/Test_MonoView/test_ExecClassifMonoView.py
index c1ddf2e5ff998fdd73c39a1539752333da6c0d76..9f380ca9b73695a4bdb414e7103f112ac6211573 100644
--- a/multiview_platform/Tests/Test_MonoView/test_ExecClassifMonoView.py
+++ b/multiview_platform/tests/Test_MonoView/test_ExecClassifMonoView.py
@@ -4,16 +4,16 @@ import unittest
 import h5py
 import numpy as np
 
-from ...MonoMultiViewClassifiers.Monoview import ExecClassifMonoView
+from ...mono_multi_view_classifiers.monoview import exec_classif_mono_view
 
 
 class Test_initConstants(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        os.mkdir("multiview_platform/Tests/temp_tests")
+        os.mkdir("multiview_platform/tests/temp_tests")
         cls.datasetFile = h5py.File(
-            "multiview_platform/Tests/temp_tests/test.hdf5", "w")
+            "multiview_platform/tests/temp_tests/test.hdf5", "w")
         cls.random_state = np.random.RandomState(42)
         cls.args = {"CL_type": "test_clf"}
         cls.X_value = cls.random_state.randint(0, 500, (10, 20))
@@ -25,7 +25,7 @@ class Test_initConstants(unittest.TestCase):
                                      np.array([1, 3, 5, 7, 9])]
         cls.labelsNames = ["test_true", "test_false"]
         cls.name = "test"
-        cls.directory = "multiview_platform/Tests/temp_tests/test_dir/"
+        cls.directory = "multiview_platform/tests/temp_tests/test_dir/"
 
     def test_simple(cls):
         kwargs, \
@@ -35,28 +35,28 @@ class Test_initConstants(unittest.TestCase):
         X, \
         learningRate, \
         labelsString, \
-        outputFileName = ExecClassifMonoView.initConstants(cls.args,
-                                                           cls.X,
-                                                           cls.classificationIndices,
-                                                           cls.labelsNames,
-                                                           cls.name,
-                                                           cls.directory)
+        outputFileName = exec_classif_mono_view.initConstants(cls.args,
+                                                              cls.X,
+                                                              cls.classificationIndices,
+                                                              cls.labelsNames,
+                                                              cls.name,
+                                                              cls.directory)
         cls.assertEqual(kwargs, cls.args)
         cls.assertEqual(feat, "test_dataset")
         cls.assertEqual(CL_type, "test_clf")
         np.testing.assert_array_equal(X, cls.X_value)
         cls.assertEqual(learningRate, 0.5)
         cls.assertEqual(labelsString, "test_true-test_false")
-        # cls.assertEqual(outputFileName, "Code/Tests/temp_tests/test_dir/test_clf/test_dataset/Results-test_clf-test_true-test_false-learnRate0.5-test-test_dataset-")
+        # cls.assertEqual(outputFileName, "Code/tests/temp_tests/test_dir/test_clf/test_dataset/results-test_clf-test_true-test_false-learnRate0.5-test-test_dataset-")
 
     @classmethod
     def tearDownClass(cls):
-        os.remove("multiview_platform/Tests/temp_tests/test.hdf5")
+        os.remove("multiview_platform/tests/temp_tests/test.hdf5")
         os.rmdir(
-            "multiview_platform/Tests/temp_tests/test_dir/test_clf/test_dataset")
-        os.rmdir("multiview_platform/Tests/temp_tests/test_dir/test_clf")
-        os.rmdir("multiview_platform/Tests/temp_tests/test_dir")
-        os.rmdir("multiview_platform/Tests/temp_tests")
+            "multiview_platform/tests/temp_tests/test_dir/test_clf/test_dataset")
+        os.rmdir("multiview_platform/tests/temp_tests/test_dir/test_clf")
+        os.rmdir("multiview_platform/tests/temp_tests/test_dir")
+        os.rmdir("multiview_platform/tests/temp_tests")
 
 
 class Test_initTrainTest(unittest.TestCase):
@@ -71,7 +71,7 @@ class Test_initTrainTest(unittest.TestCase):
                                      np.array([1, 3, 5, 7, 9])]
 
     def test_simple(cls):
-        X_train, y_train, X_test, y_test, X_test_multiclass = ExecClassifMonoView.initTrainTest(
+        X_train, y_train, X_test, y_test, X_test_multiclass = exec_classif_mono_view.initTrainTest(
             cls.X, cls.Y, cls.classificationIndices)
         np.testing.assert_array_equal(X_train, np.array(
             [np.array([102, 435, 348, 270, 106]),
diff --git a/multiview_platform/Tests/Test_MonoView/test_MonoviewUtils.py b/multiview_platform/tests/Test_MonoView/test_MonoviewUtils.py
similarity index 70%
rename from multiview_platform/Tests/Test_MonoView/test_MonoviewUtils.py
rename to multiview_platform/tests/Test_MonoView/test_MonoviewUtils.py
index d68b1c202ec3e74c044030596e6fe3d49cbb430d..da1136c66cd8c639a9c4155a261b7426384a06e2 100644
--- a/multiview_platform/Tests/Test_MonoView/test_MonoviewUtils.py
+++ b/multiview_platform/tests/Test_MonoView/test_MonoviewUtils.py
@@ -4,7 +4,7 @@ import numpy as np
 from sklearn.model_selection import StratifiedKFold
 from sklearn.tree.tree import DecisionTreeClassifier
 
-from ...MonoMultiViewClassifiers.Monoview import MonoviewUtils
+from ...mono_multi_view_classifiers.monoview import monoview_utils
 
 
 class Test_genTestFoldsPreds(unittest.TestCase):
@@ -23,10 +23,10 @@ class Test_genTestFoldsPreds(unittest.TestCase):
         # print(cls.y_train)
 
     def test_simple(cls):
-        testFoldsPreds = MonoviewUtils.genTestFoldsPreds(cls.X_train,
-                                                         cls.y_train,
-                                                         cls.KFolds,
-                                                         cls.estimator)
+        testFoldsPreds = monoview_utils.genTestFoldsPreds(cls.X_train,
+                                                          cls.y_train,
+                                                          cls.KFolds,
+                                                          cls.estimator)
         cls.assertEqual(testFoldsPreds.shape, (3, 10))
         np.testing.assert_array_equal(testFoldsPreds[0], np.array(
             [1, 1, -1, -1, 1, 1, -1, 1, -1, 1]))
diff --git a/multiview_platform/Tests/Test_MonoviewClassifiers/__init__.py b/multiview_platform/tests/Test_MonoviewClassifiers/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MonoviewClassifiers/__init__.py
rename to multiview_platform/tests/Test_MonoviewClassifiers/__init__.py
diff --git a/multiview_platform/Tests/Test_MonoviewClassifiers/test_Adaboost.py b/multiview_platform/tests/Test_MonoviewClassifiers/test_Adaboost.py
similarity index 97%
rename from multiview_platform/Tests/Test_MonoviewClassifiers/test_Adaboost.py
rename to multiview_platform/tests/Test_MonoviewClassifiers/test_Adaboost.py
index 77cc09ab3917539aebeeca97ebdf9d34352bd43d..94f5f835d05d4292a57998d9a3175d0afe6fec89 100644
--- a/multiview_platform/Tests/Test_MonoviewClassifiers/test_Adaboost.py
+++ b/multiview_platform/tests/Test_MonoviewClassifiers/test_Adaboost.py
@@ -2,7 +2,7 @@
 # import numpy as np
 # from sklearn.tree import DecisionTreeClassifier
 #
-# from ...MonoMultiViewClassifiers.MonoviewClassifiers import Adaboost
+# from ...mono_multi_view_classifiers.monoview_classifiers import Adaboost
 #
 #
 # class Test_canProbas(unittest.TestCase):
diff --git a/multiview_platform/Tests/Test_MonoviewClassifiers/test_compatibility.py b/multiview_platform/tests/Test_MonoviewClassifiers/test_compatibility.py
similarity index 82%
rename from multiview_platform/Tests/Test_MonoviewClassifiers/test_compatibility.py
rename to multiview_platform/tests/Test_MonoviewClassifiers/test_compatibility.py
index d5474eb5d5c2845fcb0991f05e3b15d3e3495a3d..d2e84d2da0deba4aa660c6e388430b7dd155b37b 100644
--- a/multiview_platform/Tests/Test_MonoviewClassifiers/test_compatibility.py
+++ b/multiview_platform/tests/Test_MonoviewClassifiers/test_compatibility.py
@@ -3,16 +3,16 @@ import unittest
 
 import numpy as np
 
-from ...MonoMultiViewClassifiers import MonoviewClassifiers
+from ...mono_multi_view_classifiers import monoview_classifiers
 
 
 class Test_methods(unittest.TestCase):
 
     def test_simple(self):
         for fileName in os.listdir(
-                "multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers"):
+                "multiview_platform/mono_multi_view_classifiers/monoview_classifiers"):
             if fileName[-3:] == ".py" and fileName != "__init__.py":
-                monoview_classifier_module = getattr(MonoviewClassifiers,
+                monoview_classifier_module = getattr(monoview_classifiers,
                                                      fileName[:-3])
                 self.assertIn("formatCmdArgs", dir(monoview_classifier_module),
                               fileName[
@@ -52,9 +52,9 @@ class Test_canProbas(unittest.TestCase):
 
     def test_outputs(self):
         for fileName in os.listdir(
-                "multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers"):
+                "multiview_platform/mono_multi_view_classifiers/monoview_classifiers"):
             if fileName[-3:] == ".py" and fileName != "__init__.py":
-                monoview_classifier_module = getattr(MonoviewClassifiers,
+                monoview_classifier_module = getattr(monoview_classifiers,
                                                      fileName[:-3])
                 monoview_classifier_class = getattr(monoview_classifier_module,
                                                     fileName[:-3])()
@@ -64,9 +64,9 @@ class Test_canProbas(unittest.TestCase):
 
     def test_inputs(self):
         for fileName in os.listdir(
-                "multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers"):
+                "multiview_platform/mono_multi_view_classifiers/monoview_classifiers"):
             if fileName[-3:] == ".py" and fileName != "__init__.py":
-                monoview_classifier_module = getattr(MonoviewClassifiers,
+                monoview_classifier_module = getattr(monoview_classifiers,
                                                      fileName[:-3])
                 monoview_classifier_class = getattr(monoview_classifier_module,
                                                     fileName[:-3])()
@@ -85,9 +85,9 @@ class Test_fit(unittest.TestCase):
 
     # def test_inputs(cls):
     #     # DATASET, CLASS_LABELS, randomState, NB_CORES=1, **kwargs
-    #     for fileName in os.listdir("Code/MonoMultiViewClassifiers/MonoviewClassifiers"):
+    #     for fileName in os.listdir("Code/mono_multi_view_classifiers/monoview_classifiers"):
     #         if fileName[-3:] == ".py" and fileName != "__init__.py":
-    #             monoview_classifier_module = getattr(MonoviewClassifiers, fileName[:-3])
+    #             monoview_classifier_module = getattr(monoview_classifiers, fileName[:-3])
     #             cls.args = dict((str(index), value) for index, value in
     #                             enumerate(monoview_classifier_module.paramsToSet(1, cls.random_state)[0]))
     #             res = monoview_classifier_module.fit(cls.dataset, cls.labels, cls.random_state, **cls.args)
@@ -98,9 +98,9 @@ class Test_fit(unittest.TestCase):
     #                 monoview_classifier_module.fit(cls.dataset,cls.labels, cls.random_state, 1, 10)
 
     # def test_outputs(cls):
-    #     for fileName in os.listdir("Code/MonoMultiViewClassifiers/MonoviewClassifiers"):
+    #     for fileName in os.listdir("Code/mono_multi_view_classifiers/monoview_classifiers"):
     #         if fileName[-3:] == ".py" and fileName != "__init__.py":
-    #             monoview_classifier_module = getattr(MonoviewClassifiers, fileName[:-3])
+    #             monoview_classifier_module = getattr(monoview_classifiers, fileName[:-3])
     #             cls.args = dict((str(index), value) for index, value in
     #                             enumerate(monoview_classifier_module.paramsToSet(1, cls.random_state)[0]))
     #             res = monoview_classifier_module.fit(cls.dataset, cls.labels, cls.random_state, **cls.args)
@@ -111,9 +111,9 @@ class Test_paramsToSet(unittest.TestCase):
 
     def test_inputs(self):
         for fileName in os.listdir(
-                "multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers"):
+                "multiview_platform/mono_multi_view_classifiers/monoview_classifiers"):
             if fileName[-3:] == ".py" and fileName != "__init__.py":
-                monoview_classifier_module = getattr(MonoviewClassifiers,
+                monoview_classifier_module = getattr(monoview_classifiers,
                                                      fileName[:-3])
                 with self.assertRaises(TypeError,
                                        msg="paramsToSet must have 2 positional args") as catcher:
@@ -128,9 +128,9 @@ class Test_paramsToSet(unittest.TestCase):
 
     def test_outputs(self):
         for fileName in os.listdir(
-                "multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers"):
+                "multiview_platform/mono_multi_view_classifiers/monoview_classifiers"):
             if fileName[-3:] == ".py" and fileName != "__init__.py":
-                monoview_classifier_module = getattr(MonoviewClassifiers,
+                monoview_classifier_module = getattr(monoview_classifiers,
                                                      fileName[:-3])
                 res = monoview_classifier_module.paramsToSet(2,
                                                              np.random.RandomState(
@@ -144,9 +144,9 @@ class Test_paramsToSet(unittest.TestCase):
 #     # TODO : Find a way to enter the right args
 #
 #     def test_inputs(self):
-#         for fileName in os.listdir("Code/MonoMultiViewClassifiers/MonoviewClassifiers"):
+#         for fileName in os.listdir("Code/mono_multi_view_classifiers/monoview_classifiers"):
 #             if fileName[-3:] == ".py" and fileName != "__init__.py":
-#                 monoview_classifier_module = getattr(MonoviewClassifiers, fileName[:-3])
+#                 monoview_classifier_module = getattr(monoview_classifiers, fileName[:-3])
 #                 with self.assertRaises(TypeError, msg="getKWARGS must have 1 positional args") as catcher:
 #                     monoview_classifier_module.getKWARGS()
 #                     monoview_classifier_module.getKWARGS([1],2)
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/test_DifficultyMeasureModule.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/test_DifficultyMeasureModule.py
similarity index 87%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/test_DifficultyMeasureModule.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/test_DifficultyMeasureModule.py
index 08462ada48a68813c20399296a1e29227d54184b..4dd7cdef6269e5c6daf9dd64a41a8159e320701e 100644
--- a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/test_DifficultyMeasureModule.py
+++ b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DifficultyMeasure/test_DifficultyMeasureModule.py
@@ -2,8 +2,8 @@ import unittest
 
 import numpy as np
 
-from ....MonoMultiViewClassifiers.MultiviewClassifiers.DifficultyFusion import \
-    DifficultyFusionModule
+from ....mono_multi_view_classifiers.multiview_classifiers.difficulty_fusion import \
+    difficulty_fusion
 
 
 class Test_difficulty(unittest.TestCase):
@@ -28,7 +28,7 @@ class Test_difficulty(unittest.TestCase):
         cls.foldsLen = ""
 
     def test_simple(cls):
-        difficulty_measure = DifficultyFusionModule.difficulty(
+        difficulty_measure = difficulty_fusion.difficulty(
             cls.classifiersDecisions,
             cls.combination,
             cls.foldsGroudTruth,
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DisagreeFusion/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DisagreeFusion/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_DisagreeFusion/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_DisagreeFusion/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DisagreeFusion/test_DisagreeFusionModule.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DisagreeFusion/test_DisagreeFusionModule.py
similarity index 91%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_DisagreeFusion/test_DisagreeFusionModule.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_DisagreeFusion/test_DisagreeFusionModule.py
index 16b809f78e39ca987e65b945f04789965d628fe9..cbc84a26a9cb85558d908fdaea98be5a3d53f41c 100644
--- a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DisagreeFusion/test_DisagreeFusionModule.py
+++ b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DisagreeFusion/test_DisagreeFusionModule.py
@@ -2,11 +2,11 @@ import unittest
 
 import numpy as np
 
-from multiview_platform.MonoMultiViewClassifiers.Multiview.Additions import \
+from multiview_platform.mono_multi_view_classifiers.multiview.Additions import \
     diversity_utils
-from ....MonoMultiViewClassifiers.MultiviewClassifiers.DisagreeFusion import \
+from ....mono_multi_view_classifiers.multiview_classifiers.disagree_fusion import \
     DisagreeFusionModule
-from multiview_platform.MonoMultiViewClassifiers.Multiview.MultiviewUtils import MultiviewResult
+from multiview_platform.mono_multi_view_classifiers.multiview.multiview_utils import MultiviewResult
 
 class Test_disagreement(unittest.TestCase):
 
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/test_DoubleFaultFusionModule.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/test_DoubleFaultFusionModule.py
similarity index 94%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/test_DoubleFaultFusionModule.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/test_DoubleFaultFusionModule.py
index ab7b9d31a43334cb24db5a186ff850f22f062b14..4a014b4e41b99f707ca86ddbe8ef539c0488bc88 100644
--- a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/test_DoubleFaultFusionModule.py
+++ b/multiview_platform/tests/Test_MultiviewClassifiers/Test_DoubleFaultFusion/test_DoubleFaultFusionModule.py
@@ -2,9 +2,9 @@ import unittest
 
 import numpy as np
 
-from multiview_platform.MonoMultiViewClassifiers.Multiview.Additions import \
+from multiview_platform.mono_multi_view_classifiers.multiview.Additions import \
     diversity_utils
-from ....MonoMultiViewClassifiers.MultiviewClassifiers.DoubleFaultFusion import \
+from ....mono_multi_view_classifiers.multiview_classifiers.double_fault_fusion import \
     DoubleFaultFusionModule
 
 
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_EntropyFusion/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_EntropyFusion/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_EntropyFusion/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_EntropyFusion/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_EntropyFusion/test_EntropyFusionModule.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_EntropyFusion/test_EntropyFusionModule.py
similarity index 94%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_EntropyFusion/test_EntropyFusionModule.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_EntropyFusion/test_EntropyFusionModule.py
index 00b4a911b9912f6ba23249e337dfa6c3c04dded4..56b374513aba498c63f7c4f0c2728ab4e4c906c1 100644
--- a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_EntropyFusion/test_EntropyFusionModule.py
+++ b/multiview_platform/tests/Test_MultiviewClassifiers/Test_EntropyFusion/test_EntropyFusionModule.py
@@ -2,7 +2,7 @@ import unittest
 
 import numpy as np
 
-from ....MonoMultiViewClassifiers.MultiviewClassifiers.EntropyFusion import \
+from ....mono_multi_view_classifiers.multiview_classifiers.entropy_fusion import \
     EntropyFusionModule
 
 
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_Fusion/Test_Methods/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_Fusion/Test_Methods/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_Fusion/Test_Methods/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_Fusion/Test_Methods/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_Fusion/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_Fusion/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_Fusion/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_Fusion/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_Fusion/test_FusionModule.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_Fusion/test_FusionModule.py
similarity index 83%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_Fusion/test_FusionModule.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_Fusion/test_FusionModule.py
index b60b2e0ed749409bc99052cf21d5d25d0c1d6d22..fc2e54bf6eb2ec3862a2ed1dd0d245616158fb44 100644
--- a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_Fusion/test_FusionModule.py
+++ b/multiview_platform/tests/Test_MultiviewClassifiers/Test_Fusion/test_FusionModule.py
@@ -1,6 +1,6 @@
 import unittest
 
-from ....MonoMultiViewClassifiers.MultiviewClassifiers.Fusion import \
+from ....mono_multi_view_classifiers.multiview_classifiers.fusion import \
     FusionModule
 
 
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/test_PseudoCQFusionModule.py b/multiview_platform/tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/test_PseudoCQFusionModule.py
similarity index 91%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/test_PseudoCQFusionModule.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/test_PseudoCQFusionModule.py
index 957cef74647fbdc8be700070de638b9c1ce5fa24..be4f271c5b9bdee74da924b037f1a58b827405fb 100644
--- a/multiview_platform/Tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/test_PseudoCQFusionModule.py
+++ b/multiview_platform/tests/Test_MultiviewClassifiers/Test_PseudoCQMeasure/test_PseudoCQFusionModule.py
@@ -2,7 +2,7 @@
 #
 # import numpy as np
 #
-# from ....MonoMultiViewClassifiers.MultiviewClassifiers.EntropyFusion import EntropyFusionModule
+# from ....mono_multi_view_classifiers.multiview_classifiers.entropy_fusion import EntropyFusionModule
 #
 # class Test_entropy(unittest.TestCase):
 #
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/__init__.py b/multiview_platform/tests/Test_MultiviewClassifiers/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/__init__.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/__init__.py
diff --git a/multiview_platform/Tests/Test_MultiviewClassifiers/test_diversity_utils.py b/multiview_platform/tests/Test_MultiviewClassifiers/test_diversity_utils.py
similarity index 94%
rename from multiview_platform/Tests/Test_MultiviewClassifiers/test_diversity_utils.py
rename to multiview_platform/tests/Test_MultiviewClassifiers/test_diversity_utils.py
index ea1c0bd88608d0e06a4fe2adc98b77bb20c9931f..98520e2e790826534e2e5c2ccd684ebb7eff7086 100644
--- a/multiview_platform/Tests/Test_MultiviewClassifiers/test_diversity_utils.py
+++ b/multiview_platform/tests/Test_MultiviewClassifiers/test_diversity_utils.py
@@ -2,7 +2,7 @@ import unittest
 
 import numpy as np
 
-from multiview_platform.MonoMultiViewClassifiers.Multiview.Additions import \
+from multiview_platform.mono_multi_view_classifiers.multiview.Additions import \
     diversity_utils
 
 
diff --git a/multiview_platform/Tests/Test_utils/__init__.py b/multiview_platform/tests/Test_utils/__init__.py
similarity index 100%
rename from multiview_platform/Tests/Test_utils/__init__.py
rename to multiview_platform/tests/Test_utils/__init__.py
diff --git a/multiview_platform/Tests/Test_utils/test_GetMultiviewDB.py b/multiview_platform/tests/Test_utils/test_GetMultiviewDB.py
similarity index 75%
rename from multiview_platform/Tests/Test_utils/test_GetMultiviewDB.py
rename to multiview_platform/tests/Test_utils/test_GetMultiviewDB.py
index 4f344d0ad3ae3baf04e1c128127482aa0f82c0be..e59ce5fbc419a28643dff535be8fb6d1347a49bc 100644
--- a/multiview_platform/Tests/Test_utils/test_GetMultiviewDB.py
+++ b/multiview_platform/tests/Test_utils/test_GetMultiviewDB.py
@@ -4,7 +4,7 @@ import unittest
 import h5py
 import numpy as np
 
-from ...MonoMultiViewClassifiers.utils import GetMultiviewDb
+from ...mono_multi_view_classifiers.utils import get_multiview_db
 
 
 class Test_copyhdf5Dataset(unittest.TestCase):
@@ -12,17 +12,17 @@ class Test_copyhdf5Dataset(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
         cls.random_state = np.random.RandomState(42)
-        if not os.path.exists("multiview_platform/Tests/temp_tests"):
-            os.mkdir("multiview_platform/Tests/temp_tests")
+        if not os.path.exists("multiview_platform/tests/temp_tests"):
+            os.mkdir("multiview_platform/tests/temp_tests")
         cls.dataset_file = h5py.File(
-            "multiview_platform/Tests/temp_tests/test_copy.hdf5", "w")
+            "multiview_platform/tests/temp_tests/test_copy.hdf5", "w")
         cls.dataset = cls.dataset_file.create_dataset("test",
                                                       data=cls.random_state.randint(
                                                           0, 100, (10, 20)))
         cls.dataset.attrs["test_arg"] = "Am I copied"
 
     def test_simple_copy(cls):
-        GetMultiviewDb.copyhdf5Dataset(cls.dataset_file, cls.dataset_file,
+        get_multiview_db.copyhdf5Dataset(cls.dataset_file, cls.dataset_file,
                                        "test", "test_copy_1", np.arange(10))
         np.testing.assert_array_equal(cls.dataset_file.get("test").value,
                                       cls.dataset_file.get("test_copy_1").value)
@@ -31,7 +31,7 @@ class Test_copyhdf5Dataset(unittest.TestCase):
 
     def test_copy_only_some_indices(cls):
         usedIndices = cls.random_state.choice(10, 6, replace=False)
-        GetMultiviewDb.copyhdf5Dataset(cls.dataset_file, cls.dataset_file,
+        get_multiview_db.copyhdf5Dataset(cls.dataset_file, cls.dataset_file,
                                        "test", "test_copy", usedIndices)
         np.testing.assert_array_equal(
             cls.dataset_file.get("test").value[usedIndices, :],
@@ -41,8 +41,8 @@ class Test_copyhdf5Dataset(unittest.TestCase):
 
     @classmethod
     def tearDownClass(cls):
-        os.remove("multiview_platform/Tests/temp_tests/test_copy.hdf5")
-        os.rmdir("multiview_platform/Tests/temp_tests")
+        os.remove("multiview_platform/tests/temp_tests/test_copy.hdf5")
+        os.rmdir("multiview_platform/tests/temp_tests")
 
 
 class Test_filterViews(unittest.TestCase):
@@ -51,10 +51,10 @@ class Test_filterViews(unittest.TestCase):
     def setUpClass(cls):
         cls.random_state = np.random.RandomState(42)
         cls.views = ["test_view_1", "test_view_2"]
-        if not os.path.exists("multiview_platform/Tests/temp_tests"):
-            os.mkdir("multiview_platform/Tests/temp_tests")
+        if not os.path.exists("multiview_platform/tests/temp_tests"):
+            os.mkdir("multiview_platform/tests/temp_tests")
         cls.dataset_file = h5py.File(
-            "multiview_platform/Tests/temp_tests/test_copy.hdf5", "w")
+            "multiview_platform/tests/temp_tests/test_copy.hdf5", "w")
         cls.metadata_group = cls.dataset_file.create_group("Metadata")
         cls.metadata_group.attrs["nbView"] = 4
 
@@ -66,10 +66,10 @@ class Test_filterViews(unittest.TestCase):
 
     def test_simple_filter(cls):
         cls.temp_dataset_file = h5py.File(
-            "multiview_platform/Tests/temp_tests/test_copy_temp.hdf5", "w")
+            "multiview_platform/tests/temp_tests/test_copy_temp.hdf5", "w")
         cls.dataset_file.copy("Metadata", cls.temp_dataset_file)
-        GetMultiviewDb.filterViews(cls.dataset_file, cls.temp_dataset_file,
-                                   cls.views, np.arange(10))
+        get_multiview_db.filterViews(cls.dataset_file, cls.temp_dataset_file,
+                                     cls.views, np.arange(10))
         cls.assertEqual(cls.dataset_file.get("View1").attrs["name"],
                         cls.temp_dataset_file.get("View0").attrs["name"])
         np.testing.assert_array_equal(cls.dataset_file.get("View2").value,
@@ -79,11 +79,11 @@ class Test_filterViews(unittest.TestCase):
 
     def test_filter_view_and_examples(cls):
         cls.temp_dataset_file = h5py.File(
-            "multiview_platform/Tests/temp_tests/test_copy_temp.hdf5", "w")
+            "multiview_platform/tests/temp_tests/test_copy_temp.hdf5", "w")
         cls.dataset_file.copy("Metadata", cls.temp_dataset_file)
         usedIndices = cls.random_state.choice(10, 6, replace=False)
-        GetMultiviewDb.filterViews(cls.dataset_file, cls.temp_dataset_file,
-                                   cls.views, usedIndices)
+        get_multiview_db.filterViews(cls.dataset_file, cls.temp_dataset_file,
+                                     cls.views, usedIndices)
         np.testing.assert_array_equal(
             cls.dataset_file.get("View1").value[usedIndices, :],
             cls.temp_dataset_file.get("View0").value)
@@ -91,9 +91,9 @@ class Test_filterViews(unittest.TestCase):
 
     @classmethod
     def tearDownClass(cls):
-        os.remove("multiview_platform/Tests/temp_tests/test_copy.hdf5")
-        os.remove("multiview_platform/Tests/temp_tests/test_copy_temp.hdf5")
-        os.rmdir("multiview_platform/Tests/temp_tests")
+        os.remove("multiview_platform/tests/temp_tests/test_copy.hdf5")
+        os.remove("multiview_platform/tests/temp_tests/test_copy_temp.hdf5")
+        os.rmdir("multiview_platform/tests/temp_tests")
 
 
 #
@@ -112,11 +112,11 @@ class Test_filterLabels(unittest.TestCase):
     def test_simple(cls):
         newLabels, \
         newLabelsNames, \
-        usedIndices = GetMultiviewDb.filterLabels(cls.labelsSet,
-                                                  cls.askedLabelsNamesSet,
-                                                  cls.fullLabels,
-                                                  cls.availableLabelsNames,
-                                                  cls.askedLabelsNames)
+        usedIndices = get_multiview_db.filterLabels(cls.labelsSet,
+                                                    cls.askedLabelsNamesSet,
+                                                    cls.fullLabels,
+                                                    cls.availableLabelsNames,
+                                                    cls.askedLabelsNames)
         cls.assertEqual(["test_label_1", "test_label_3"], newLabelsNames)
         np.testing.assert_array_equal(usedIndices, np.array([1, 5, 9]))
         np.testing.assert_array_equal(newLabels, np.array([1, 1, 0]))
@@ -127,11 +127,11 @@ class Test_filterLabels(unittest.TestCase):
         cls.availableLabelsNames = ["test_label_0", "test_label_1"]
         newLabels, \
         newLabelsNames, \
-        usedIndices = GetMultiviewDb.filterLabels(cls.labelsSet,
-                                                  cls.askedLabelsNamesSet,
-                                                  cls.fullLabels,
-                                                  cls.availableLabelsNames,
-                                                  cls.askedLabelsNames)
+        usedIndices = get_multiview_db.filterLabels(cls.labelsSet,
+                                                    cls.askedLabelsNamesSet,
+                                                    cls.fullLabels,
+                                                    cls.availableLabelsNames,
+                                                    cls.askedLabelsNames)
         cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
         np.testing.assert_array_equal(usedIndices, np.arange(10))
         np.testing.assert_array_equal(newLabels, cls.fullLabels)
@@ -140,12 +140,12 @@ class Test_filterLabels(unittest.TestCase):
         cls.askedLabelsNamesSet = {"test_label_0", "test_label_1",
                                    "test_label_2", "test_label_3",
                                    "chicken_is_heaven"}
-        with cls.assertRaises(GetMultiviewDb.DatasetError) as catcher:
-            GetMultiviewDb.filterLabels(cls.labelsSet,
-                                        cls.askedLabelsNamesSet,
-                                        cls.fullLabels,
-                                        cls.availableLabelsNames,
-                                        cls.askedLabelsNames)
+        with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
+            get_multiview_db.filterLabels(cls.labelsSet,
+                                          cls.askedLabelsNamesSet,
+                                          cls.fullLabels,
+                                          cls.availableLabelsNames,
+                                          cls.askedLabelsNames)
         exception = catcher.exception
 
     def test_asked_all_labels(cls):
@@ -155,11 +155,11 @@ class Test_filterLabels(unittest.TestCase):
                                 "test_label_3"]
         newLabels, \
         newLabelsNames, \
-        usedIndices = GetMultiviewDb.filterLabels(cls.labelsSet,
-                                                  cls.askedLabelsNamesSet,
-                                                  cls.fullLabels,
-                                                  cls.availableLabelsNames,
-                                                  cls.askedLabelsNames)
+        usedIndices = get_multiview_db.filterLabels(cls.labelsSet,
+                                                    cls.askedLabelsNamesSet,
+                                                    cls.fullLabels,
+                                                    cls.availableLabelsNames,
+                                                    cls.askedLabelsNames)
         cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
         np.testing.assert_array_equal(usedIndices, np.arange(10))
         np.testing.assert_array_equal(newLabels, cls.fullLabels)
@@ -179,10 +179,10 @@ class Test_selectAskedLabels(unittest.TestCase):
     def test_simple(cls):
         newLabels, \
         newLabelsNames, \
-        usedIndices = GetMultiviewDb.selectAskedLabels(cls.askedLabelsNamesSet,
-                                                       cls.availableLabelsNames,
-                                                       cls.askedLabelsNames,
-                                                       cls.fullLabels)
+        usedIndices = get_multiview_db.selectAskedLabels(cls.askedLabelsNamesSet,
+                                                         cls.availableLabelsNames,
+                                                         cls.askedLabelsNames,
+                                                         cls.fullLabels)
         cls.assertEqual(["test_label_1", "test_label_3"], newLabelsNames)
         np.testing.assert_array_equal(usedIndices, np.array([1, 5, 9]))
         np.testing.assert_array_equal(newLabels, np.array([1, 1, 0]))
@@ -194,10 +194,10 @@ class Test_selectAskedLabels(unittest.TestCase):
                                 "test_label_3"]
         newLabels, \
         newLabelsNames, \
-        usedIndices = GetMultiviewDb.selectAskedLabels(cls.askedLabelsNamesSet,
-                                                       cls.availableLabelsNames,
-                                                       cls.askedLabelsNames,
-                                                       cls.fullLabels)
+        usedIndices = get_multiview_db.selectAskedLabels(cls.askedLabelsNamesSet,
+                                                         cls.availableLabelsNames,
+                                                         cls.askedLabelsNames,
+                                                         cls.fullLabels)
         cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
         np.testing.assert_array_equal(usedIndices, np.arange(10))
         np.testing.assert_array_equal(newLabels, cls.fullLabels)
@@ -205,11 +205,11 @@ class Test_selectAskedLabels(unittest.TestCase):
     def test_asked_unavailable_labels(cls):
         cls.askedLabelsNamesSet = {"test_label_1", "test_label_3",
                                    "chicken_is_heaven"}
-        with cls.assertRaises(GetMultiviewDb.DatasetError) as catcher:
-            GetMultiviewDb.selectAskedLabels(cls.askedLabelsNamesSet,
-                                             cls.availableLabelsNames,
-                                             cls.askedLabelsNames,
-                                             cls.fullLabels)
+        with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
+            get_multiview_db.selectAskedLabels(cls.askedLabelsNamesSet,
+                                               cls.availableLabelsNames,
+                                               cls.askedLabelsNames,
+                                               cls.fullLabels)
         exception = catcher.exception
         # cls.assertTrue("Asked labels are not all available in the dataset" in exception)
 
@@ -224,7 +224,7 @@ class Test_getAllLabels(unittest.TestCase):
                                     "test_label_2", "test_label_3"]
 
     def test_simple(cls):
-        newLabels, newLabelsNames, usedIndices = GetMultiviewDb.getAllLabels(
+        newLabels, newLabelsNames, usedIndices = get_multiview_db.getAllLabels(
             cls.fullLabels, cls.availableLabelsNames)
         cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
         np.testing.assert_array_equal(usedIndices, np.arange(10))
@@ -241,7 +241,7 @@ class Test_fillLabelNames(unittest.TestCase):
         cls.availableLabelsNames = ["test_label_" + str(_) for _ in range(40)]
 
     def test_simple(cls):
-        askedLabelsNames, askedLabelsNamesSet = GetMultiviewDb.fillLabelNames(
+        askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fillLabelNames(
             cls.NB_CLASS,
             cls.askedLabelsNames,
             cls.randomState,
@@ -251,7 +251,7 @@ class Test_fillLabelNames(unittest.TestCase):
 
     def test_missing_labels_names(cls):
         cls.NB_CLASS = 39
-        askedLabelsNames, askedLabelsNamesSet = GetMultiviewDb.fillLabelNames(
+        askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fillLabelNames(
             cls.NB_CLASS,
             cls.askedLabelsNames,
             cls.randomState,
@@ -279,7 +279,7 @@ class Test_fillLabelNames(unittest.TestCase):
         cls.NB_CLASS = 2
         cls.askedLabelsNames = ["test_label_1", "test_label_3", "test_label_4",
                                 "test_label_6"]
-        askedLabelsNames, askedLabelsNamesSet = GetMultiviewDb.fillLabelNames(
+        askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fillLabelNames(
             cls.NB_CLASS,
             cls.askedLabelsNames,
             cls.randomState,
@@ -298,15 +298,15 @@ class Test_allAskedLabelsAreAvailable(unittest.TestCase):
 
     def test_asked_available_labels(cls):
         cls.assertTrue(
-            GetMultiviewDb.allAskedLabelsAreAvailable(cls.askedLabelsNamesSet,
-                                                      cls.availableLabelsNames))
+            get_multiview_db.allAskedLabelsAreAvailable(cls.askedLabelsNamesSet,
+                                                        cls.availableLabelsNames))
 
     def test_asked_unavailable_label(cls):
         cls.askedLabelsNamesSet = {"test_label_1", "test_label_3",
                                    "chicken_is_heaven"}
         cls.assertFalse(
-            GetMultiviewDb.allAskedLabelsAreAvailable(cls.askedLabelsNamesSet,
-                                                      cls.availableLabelsNames))
+            get_multiview_db.allAskedLabelsAreAvailable(cls.askedLabelsNamesSet,
+                                                        cls.availableLabelsNames))
 
 
 class Test_getClasses(unittest.TestCase):
@@ -316,18 +316,18 @@ class Test_getClasses(unittest.TestCase):
         cls.random_state = np.random.RandomState(42)
 
     def test_multiclass(cls):
-        labelsSet = GetMultiviewDb.getClasses(
+        labelsSet = get_multiview_db.getClasses(
             cls.random_state.randint(0, 5, 30))
         cls.assertEqual(labelsSet, {0, 1, 2, 3, 4})
 
     def test_biclass(cls):
-        labelsSet = GetMultiviewDb.getClasses(
+        labelsSet = get_multiview_db.getClasses(
             cls.random_state.randint(0, 2, 30))
         cls.assertEqual(labelsSet, {0, 1})
 
     def test_one_class(cls):
-        with cls.assertRaises(GetMultiviewDb.DatasetError) as catcher:
-            GetMultiviewDb.getClasses(np.zeros(30, dtype=int))
+        with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
+            get_multiview_db.getClasses(np.zeros(30, dtype=int))
         exception = catcher.exception
         # cls.assertTrue("Dataset must have at least two different labels" in exception)
 
@@ -336,11 +336,11 @@ class Test_getClassicDBhdf5(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        if not os.path.exists("multiview_platform/Tests/temp_tests"):
-            os.mkdir("multiview_platform/Tests/temp_tests")
+        if not os.path.exists("multiview_platform/tests/temp_tests"):
+            os.mkdir("multiview_platform/tests/temp_tests")
         cls.dataset_file = h5py.File(
-            "multiview_platform/Tests/temp_tests/test_dataset.hdf5", "w")
-        cls.pathF = "multiview_platform/Tests/temp_tests/"
+            "multiview_platform/tests/temp_tests/test_dataset.hdf5", "w")
+        cls.pathF = "multiview_platform/tests/temp_tests/"
         cls.nameDB = "test_dataset"
         cls.NB_CLASS = 2
         cls.askedLabelsNames = ["test_label_1", "test_label_3"]
@@ -363,7 +363,7 @@ class Test_getClassicDBhdf5(unittest.TestCase):
             cls.dataset.attrs["name"] = "test_view_" + str(i)
 
     def test_simple(cls):
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBhdf5(
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(
             cls.views, cls.pathF, cls.nameDB,
             cls.NB_CLASS, cls.askedLabelsNames,
             cls.random_state)
@@ -381,7 +381,7 @@ class Test_getClassicDBhdf5(unittest.TestCase):
         askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
                             "test_label_3"]
         NB_CLASS = 4
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBhdf5(
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(
             cls.views, cls.pathF, cls.nameDB,
             NB_CLASS, askedLabelsNames,
             cls.random_state)
@@ -398,12 +398,12 @@ class Test_getClassicDBhdf5(unittest.TestCase):
 
     def test_all_views_asked(cls):
         views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBhdf5(views,
-                                                                          cls.pathF,
-                                                                          cls.nameDB,
-                                                                          cls.NB_CLASS,
-                                                                          cls.askedLabelsNames,
-                                                                          cls.random_state)
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(views,
+                                                                                          cls.pathF,
+                                                                                          cls.nameDB,
+                                                                                          cls.NB_CLASS,
+                                                                                          cls.askedLabelsNames,
+                                                                                          cls.random_state)
         for viewIndex in range(4):
             np.testing.assert_array_equal(
                 dataset_file.get("View" + str(viewIndex)).value,
@@ -423,12 +423,12 @@ class Test_getClassicDBhdf5(unittest.TestCase):
                             "test_label_3"]
         NB_CLASS = 4
         views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBhdf5(views,
-                                                                          cls.pathF,
-                                                                          cls.nameDB,
-                                                                          NB_CLASS,
-                                                                          askedLabelsNames,
-                                                                          cls.random_state)
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(views,
+                                                                                          cls.pathF,
+                                                                                          cls.nameDB,
+                                                                                          NB_CLASS,
+                                                                                          askedLabelsNames,
+                                                                                          cls.random_state)
         for viewIndex in range(4):
             np.testing.assert_array_equal(
                 dataset_file.get("View" + str(viewIndex)).value,
@@ -446,21 +446,21 @@ class Test_getClassicDBhdf5(unittest.TestCase):
     @classmethod
     def tearDownClass(cls):
         os.remove(
-            "multiview_platform/Tests/temp_tests/test_dataset_temp_view_label_select.hdf5")
-        os.remove("multiview_platform/Tests/temp_tests/test_dataset.hdf5")
-        dirs = os.listdir("multiview_platform/Tests/temp_tests")
+            "multiview_platform/tests/temp_tests/test_dataset_temp_view_label_select.hdf5")
+        os.remove("multiview_platform/tests/temp_tests/test_dataset.hdf5")
+        dirs = os.listdir("multiview_platform/tests/temp_tests")
         for dir in dirs:
             print(dir)
-        os.rmdir("multiview_platform/Tests/temp_tests")
+        os.rmdir("multiview_platform/tests/temp_tests")
 
 
 class Test_getClassicDBcsv(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        if not os.path.exists("multiview_platform/Tests/temp_tests"):
-            os.mkdir("multiview_platform/Tests/temp_tests")
-        cls.pathF = "multiview_platform/Tests/temp_tests/"
+        if not os.path.exists("multiview_platform/tests/temp_tests"):
+            os.mkdir("multiview_platform/tests/temp_tests")
+        cls.pathF = "multiview_platform/tests/temp_tests/"
         cls.NB_CLASS = 2
         cls.nameDB = "test_dataset"
         cls.askedLabelsNames = ["test_label_1", "test_label_3"]
@@ -481,7 +481,7 @@ class Test_getClassicDBcsv(unittest.TestCase):
             cls.datas.append(data)
 
     def test_simple(cls):
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBcsv(
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(
             cls.views, cls.pathF, cls.nameDB,
             cls.NB_CLASS, cls.askedLabelsNames,
             cls.random_state, delimiter=",")
@@ -497,13 +497,13 @@ class Test_getClassicDBcsv(unittest.TestCase):
 
     def test_all_views_asked(cls):
         views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBcsv(views,
-                                                                         cls.pathF,
-                                                                         cls.nameDB,
-                                                                         cls.NB_CLASS,
-                                                                         cls.askedLabelsNames,
-                                                                         cls.random_state,
-                                                                         delimiter=",")
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(views,
+                                                                                         cls.pathF,
+                                                                                         cls.nameDB,
+                                                                                         cls.NB_CLASS,
+                                                                                         cls.askedLabelsNames,
+                                                                                         cls.random_state,
+                                                                                         delimiter=",")
         cls.assertEqual(labels_dictionary,
                         {0: "test_label_1", 1: "test_label_3"})
         cls.assertEqual(dataset_file.get("Metadata").attrs["datasetLength"], 3)
@@ -522,7 +522,7 @@ class Test_getClassicDBcsv(unittest.TestCase):
         askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
                             "test_label_3"]
         NB_CLASS = 4
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBcsv(
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(
             cls.views, cls.pathF, cls.nameDB,
             NB_CLASS, askedLabelsNames,
             cls.random_state, delimiter=",")
@@ -541,13 +541,13 @@ class Test_getClassicDBcsv(unittest.TestCase):
                             "test_label_3"]
         NB_CLASS = 4
         views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
-        dataset_file, labels_dictionary, dataset_name = GetMultiviewDb.getClassicDBcsv(views,
-                                                                         cls.pathF,
-                                                                         cls.nameDB,
-                                                                         NB_CLASS,
-                                                                         askedLabelsNames,
-                                                                         cls.random_state,
-                                                                         delimiter=",")
+        dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(views,
+                                                                                         cls.pathF,
+                                                                                         cls.nameDB,
+                                                                                         NB_CLASS,
+                                                                                         askedLabelsNames,
+                                                                                         cls.random_state,
+                                                                                         delimiter=",")
         for viewIndex in range(4):
             np.testing.assert_array_equal(
                 dataset_file.get("View" + str(viewIndex)).value,
@@ -566,15 +566,15 @@ class Test_getClassicDBcsv(unittest.TestCase):
     def tearDownClass(cls):
         for i in range(4):
             os.remove(
-                "multiview_platform/Tests/temp_tests/Views/test_view_" + str(
+                "multiview_platform/tests/temp_tests/Views/test_view_" + str(
                     i) + ".csv")
-        os.rmdir("multiview_platform/Tests/temp_tests/Views")
+        os.rmdir("multiview_platform/tests/temp_tests/Views")
         os.remove(
-            "multiview_platform/Tests/temp_tests/test_dataset-labels-names.csv")
-        os.remove("multiview_platform/Tests/temp_tests/test_dataset-labels.csv")
-        os.remove("multiview_platform/Tests/temp_tests/test_dataset.hdf5")
+            "multiview_platform/tests/temp_tests/test_dataset-labels-names.csv")
+        os.remove("multiview_platform/tests/temp_tests/test_dataset-labels.csv")
+        os.remove("multiview_platform/tests/temp_tests/test_dataset.hdf5")
         os.remove(
-            "multiview_platform/Tests/temp_tests/test_dataset_temp_view_label_select.hdf5")
-        for file in os.listdir("multiview_platform/Tests/temp_tests"): print(
+            "multiview_platform/tests/temp_tests/test_dataset_temp_view_label_select.hdf5")
+        for file in os.listdir("multiview_platform/tests/temp_tests"): print(
             file)
-        os.rmdir("multiview_platform/Tests/temp_tests")
+        os.rmdir("multiview_platform/tests/temp_tests")
diff --git a/multiview_platform/Tests/Test_utils/test_execution.py b/multiview_platform/tests/Test_utils/test_execution.py
similarity index 89%
rename from multiview_platform/Tests/Test_utils/test_execution.py
rename to multiview_platform/tests/Test_utils/test_execution.py
index b2beaf5e163002dfd7f86522c9972038e3c38e03..003b928bccd7816d0b84d86249fece750c4c2abe 100644
--- a/multiview_platform/Tests/Test_utils/test_execution.py
+++ b/multiview_platform/tests/Test_utils/test_execution.py
@@ -3,7 +3,7 @@ import unittest
 
 import numpy as np
 
-from ...MonoMultiViewClassifiers.utils import execution
+from ...mono_multi_view_classifiers.utils import execution
 
 
 class Test_parseTheArgs(unittest.TestCase):
@@ -52,14 +52,14 @@ class Test_getDatabaseFunction(unittest.TestCase):
 
     def test_simple(cls):
         getDB = execution.getDatabaseFunction(cls.name, cls.type)
-        from ...MonoMultiViewClassifiers.utils.GetMultiviewDb import \
+        from ...mono_multi_view_classifiers.utils.get_multiview_db import \
             getClassicDBcsv
         cls.assertEqual(getDB, getClassicDBcsv)
 
     def test_hdf5(cls):
         cls.type = ".hdf5"
         getDB = execution.getDatabaseFunction(cls.name, cls.type)
-        from ...MonoMultiViewClassifiers.utils.GetMultiviewDb import \
+        from ...mono_multi_view_classifiers.utils.get_multiview_db import \
             getClassicDBhdf5
         cls.assertEqual(getDB, getClassicDBhdf5)
 
@@ -67,7 +67,7 @@ class Test_getDatabaseFunction(unittest.TestCase):
         cls.name = "Plausible"
         cls.type = ".hdf5"
         getDB = execution.getDatabaseFunction(cls.name, cls.type)
-        from ...MonoMultiViewClassifiers.utils.GetMultiviewDb import \
+        from ...mono_multi_view_classifiers.utils.get_multiview_db import \
             getPlausibleDBhdf5
         cls.assertEqual(getDB, getPlausibleDBhdf5)
 
@@ -75,26 +75,26 @@ class Test_getDatabaseFunction(unittest.TestCase):
 class Test_initRandomState(unittest.TestCase):
 
     def setUp(self):
-        os.mkdir("multiview_platform/Tests/temp_tests/")
+        os.mkdir("multiview_platform/tests/temp_tests/")
 
     def tearDown(self):
-        os.rmdir("multiview_platform/Tests/temp_tests/")
+        os.rmdir("multiview_platform/tests/temp_tests/")
 
     def test_random_state_42(self):
         randomState_42 = np.random.RandomState(42)
         randomState = execution.initRandomState("42",
-                                                "multiview_platform/Tests/temp_tests/")
-        os.remove("multiview_platform/Tests/temp_tests/randomState.pickle")
+                                                "multiview_platform/tests/temp_tests/")
+        os.remove("multiview_platform/tests/temp_tests/randomState.pickle")
         np.testing.assert_array_equal(randomState.beta(1, 100, 100),
                                       randomState_42.beta(1, 100, 100))
 
     def test_random_state_pickle(self):
         randomState_to_pickle = execution.initRandomState(None,
-                                                          "multiview_platform/Tests/temp_tests/")
+                                                          "multiview_platform/tests/temp_tests/")
         pickled_randomState = execution.initRandomState(
-            "multiview_platform/Tests/temp_tests/randomState.pickle",
-            "multiview_platform/Tests/temp_tests/")
-        os.remove("multiview_platform/Tests/temp_tests/randomState.pickle")
+            "multiview_platform/tests/temp_tests/randomState.pickle",
+            "multiview_platform/tests/temp_tests/")
+        os.remove("multiview_platform/tests/temp_tests/randomState.pickle")
         np.testing.assert_array_equal(randomState_to_pickle.beta(1, 100, 100),
                                       pickled_randomState.beta(1, 100, 100))
 
@@ -119,14 +119,14 @@ class FakeArg():
 #     def test_initLogFile(cls):
 #         cls.timestr = time.strftime("%Y_%m_%d-%H_%M")
 #         execution.initLogFile(cls.fakeArgs)
-#         cls.assertIn("zrtTap", os.listdir("mutliview_platform/Results"), "Database directory not created")
-#         cls.assertIn("started_"+cls.timestr, os.listdir("mutliview_platform/Results/zrtTap"),"experimentation dir not created")
+#         cls.assertIn("zrtTap", os.listdir("mutliview_platform/results"), "Database directory not created")
+#         cls.assertIn("started_"+cls.timestr, os.listdir("mutliview_platform/results/zrtTap"),"experimentation dir not created")
 #         cls.assertIn(cls.timestr + "-" + ''.join(cls.fakeArgs.CL_type) + "-" + "_".join(
-#         cls.fakeArgs.views) + "-" + cls.fakeArgs.name + "-LOG.log", os.listdir("mutliview_platform/Results/zrtTap/"+"started_"+cls.timestr), "logfile was not created")
+#         cls.fakeArgs.views) + "-" + cls.fakeArgs.name + "-LOG.log", os.listdir("mutliview_platform/results/zrtTap/"+"started_"+cls.timestr), "logfile was not created")
 #
 #     @classmethod
 #     def tearDownClass(cls):
-#         shutil.rmtree("multiview_platform/Results/zrtTap")
+#         shutil.rmtree("multiview_platform/results/zrtTap")
 #         pass
 
 
diff --git a/multiview_platform/Tests/Test_utils/test_multiclass.py b/multiview_platform/tests/Test_utils/test_multiclass.py
similarity index 95%
rename from multiview_platform/Tests/Test_utils/test_multiclass.py
rename to multiview_platform/tests/Test_utils/test_multiclass.py
index c6bcc6ca532c1a96c3855211602c0c5405669907..a73e9f2b044dd8cd42c534e21d610ba384a897ec 100644
--- a/multiview_platform/Tests/Test_utils/test_multiclass.py
+++ b/multiview_platform/tests/Test_utils/test_multiclass.py
@@ -2,7 +2,7 @@ import unittest
 
 import numpy as np
 
-from ...MonoMultiViewClassifiers.utils import Multiclass
+from ...mono_multi_view_classifiers.utils import multiclass
 
 
 class Test_genMulticlassLabels(unittest.TestCase):
@@ -21,7 +21,7 @@ class Test_genMulticlassLabels(unittest.TestCase):
              cls.testIndices[1]]]
 
     def test_one_versus_one(cls):
-        multiclassLabels, labelsIndices, oldIndicesMulticlass = Multiclass.genMulticlassLabels(
+        multiclassLabels, labelsIndices, oldIndicesMulticlass = multiclass.genMulticlassLabels(
             cls.labels, "oneVersusOne", cls.classificationIndices)
         cls.assertEqual(len(multiclassLabels), 10)
         cls.assertEqual(labelsIndices,
diff --git a/multiview_platform/Tests/__init__.py b/multiview_platform/tests/__init__.py
similarity index 100%
rename from multiview_platform/Tests/__init__.py
rename to multiview_platform/tests/__init__.py
diff --git a/multiview_platform/Tests/test_ExecClassif.py b/multiview_platform/tests/test_ExecClassif.py
similarity index 82%
rename from multiview_platform/Tests/test_ExecClassif.py
rename to multiview_platform/tests/test_ExecClassif.py
index c9e6416adb0dd54ebb7794b3609ad90939d957d7..77bcda5fccccb06f9d922c8836b9fbea99f5c029 100644
--- a/multiview_platform/Tests/test_ExecClassif.py
+++ b/multiview_platform/tests/test_ExecClassif.py
@@ -4,7 +4,7 @@ import unittest
 import h5py
 import numpy as np
 
-from ..MonoMultiViewClassifiers import ExecClassif
+from ..mono_multi_view_classifiers import exec_classif
 
 
 class Test_initBenchmark(unittest.TestCase):
@@ -17,21 +17,21 @@ class Test_initBenchmark(unittest.TestCase):
 class Test_initKWARGS(unittest.TestCase):
 
     def test_initKWARGSFunc_no_monoview(self):
-        benchmark = {"Monoview": {}, "Multiview": {}}
-        args = ExecClassif.initKWARGSFunc({}, benchmark)
+        benchmark = {"monoview": {}, "multiview": {}}
+        args = exec_classif.initKWARGSFunc({}, benchmark)
         self.assertEqual(args, {})
 
 
 class Test_initMonoviewArguments(unittest.TestCase):
 
     def test_initMonoviewArguments_no_monoview(self):
-        benchmark = {"Monoview": {}, "Multiview": {}}
-        arguments = ExecClassif.initMonoviewExps(benchmark, {}, 0, {})
-        self.assertEqual(arguments, {'Monoview': [], 'Multiview': []})
+        benchmark = {"monoview": {}, "multiview": {}}
+        arguments = exec_classif.initMonoviewExps(benchmark, {}, 0, {})
+        self.assertEqual(arguments, {'monoview': [], 'multiview': []})
 
     def test_initMonoviewArguments_empty(self):
-        benchmark = {"Monoview": {}, "Multiview": {}}
-        arguments = ExecClassif.initMonoviewExps(benchmark, {}, 0, {})
+        benchmark = {"monoview": {}, "multiview": {}}
+        arguments = exec_classif.initMonoviewExps(benchmark, {}, 0, {})
 
 
 def fakeBenchmarkExec(coreIndex=-1, a=7, args=1):
@@ -61,35 +61,35 @@ class Test_execBenchmark(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        os.mkdir("multiview_platform/Tests/tmp_tests")
+        os.mkdir("multiview_platform/tests/tmp_tests")
         cls.Dataset = h5py.File(
-            "multiview_platform/Tests/tmp_tests/test_file.hdf5", "w")
+            "multiview_platform/tests/tmp_tests/test_file.hdf5", "w")
         cls.labels = cls.Dataset.create_dataset("Labels",
                                                 data=np.array([0, 1, 2]))
         cls.argumentDictionaries = [{"a": 4, "args": FakeArg()}]
 
     def test_simple(cls):
-        res = ExecClassif.execBenchmark(1, 2, 3, cls.argumentDictionaries,
-                                        [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
-                                        10, cls.Dataset,
-                                        execOneBenchmark=fakeBenchmarkExec,
-                                        execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
-                                        execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
-                                        getResults=fakegetResults,
-                                        delete=fakeDelete)
+        res = exec_classif.execBenchmark(1, 2, 3, cls.argumentDictionaries,
+                                         [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
+                                         10, cls.Dataset,
+                                         execOneBenchmark=fakeBenchmarkExec,
+                                         execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
+                                         execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
+                                         getResults=fakegetResults,
+                                         delete=fakeDelete)
         cls.assertEqual(res, 3)
 
     def test_multiclass_no_iter(cls):
         cls.argumentDictionaries = [{"a": 10, "args": FakeArg()},
                                     {"a": 4, "args": FakeArg()}]
-        res = ExecClassif.execBenchmark(2, 1, 2, cls.argumentDictionaries,
-                                        [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
-                                        10, cls.Dataset,
-                                        execOneBenchmark=fakeBenchmarkExec,
-                                        execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
-                                        execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
-                                        getResults=fakegetResults,
-                                        delete=fakeDelete)
+        res = exec_classif.execBenchmark(2, 1, 2, cls.argumentDictionaries,
+                                         [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
+                                         10, cls.Dataset,
+                                         execOneBenchmark=fakeBenchmarkExec,
+                                         execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
+                                         execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
+                                         getResults=fakegetResults,
+                                         delete=fakeDelete)
         cls.assertEqual(res, 3)
 
     def test_multiclass_and_iter(cls):
@@ -97,32 +97,32 @@ class Test_execBenchmark(unittest.TestCase):
                                     {"a": 4, "args": FakeArg()},
                                     {"a": 55, "args": FakeArg()},
                                     {"a": 24, "args": FakeArg()}]
-        res = ExecClassif.execBenchmark(2, 2, 2, cls.argumentDictionaries,
-                                        [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
-                                        10, cls.Dataset,
-                                        execOneBenchmark=fakeBenchmarkExec,
-                                        execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
-                                        execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
-                                        getResults=fakegetResults,
-                                        delete=fakeDelete)
+        res = exec_classif.execBenchmark(2, 2, 2, cls.argumentDictionaries,
+                                         [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
+                                         10, cls.Dataset,
+                                         execOneBenchmark=fakeBenchmarkExec,
+                                         execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
+                                         execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
+                                         getResults=fakegetResults,
+                                         delete=fakeDelete)
         cls.assertEqual(res, 3)
 
     def test_no_iter_biclass_multicore(cls):
-        res = ExecClassif.execBenchmark(2, 1, 1, cls.argumentDictionaries,
-                                        [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
-                                        10, cls.Dataset,
-                                        execOneBenchmark=fakeBenchmarkExec,
-                                        execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
-                                        execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
-                                        getResults=fakegetResults,
-                                        delete=fakeDelete)
+        res = exec_classif.execBenchmark(2, 1, 1, cls.argumentDictionaries,
+                                         [[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
+                                         10, cls.Dataset,
+                                         execOneBenchmark=fakeBenchmarkExec,
+                                         execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
+                                         execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
+                                         getResults=fakegetResults,
+                                         delete=fakeDelete)
         cls.assertEqual(res, 3)
 
     @classmethod
     def tearDownClass(cls):
         cls.Dataset.close()
-        os.remove("multiview_platform/Tests/tmp_tests/test_file.hdf5")
-        os.rmdir("multiview_platform/Tests/tmp_tests")
+        os.remove("multiview_platform/tests/tmp_tests/test_file.hdf5")
+        os.rmdir("multiview_platform/tests/tmp_tests")
 
 
 def fakeExecMono(directory, name, labelsNames, classificationIndices, kFolds,
@@ -141,8 +141,8 @@ def fakeExecMulti(directory, coreIndex, name, classificationIndices, kFolds,
 def fakeInitMulti(args, benchmark, views, viewsIndices, argumentDictionaries,
                   randomState, directory, resultsMonoview,
                   classificationIndices):
-    return {"Monoview": [{"try": 0}, {"try2": 100}],
-            "Multiview": [{"try3": 5}, {"try4": 10}]}
+    return {"monoview": [{"try": 0}, {"try2": 100}],
+            "multiview": [{"try3": 5}, {"try4": 10}]}
 
 
 class FakeArg(object):
@@ -166,40 +166,40 @@ class Test_execOneBenchmark(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        os.mkdir("multiview_platform/Tests/tmp_tests")
+        os.mkdir("multiview_platform/tests/tmp_tests")
 
     def test_simple(cls):
-        flag, results = ExecClassif.execOneBenchmark(coreIndex=10,
-                                                               LABELS_DICTIONARY={
+        flag, results = exec_classif.execOneBenchmark(coreIndex=10,
+                                                      LABELS_DICTIONARY={
                                                                    0: "a",
                                                                    1: "b"},
-                                                               directory="multiview_platform/Tests/tmp_tests/",
-                                                               classificationIndices=(
+                                                      directory="multiview_platform/tests/tmp_tests/",
+                                                      classificationIndices=(
                                                                [1, 2, 3, 4],
                                                                [0, 5, 6, 7, 8]),
-                                                               args=FakeArg(),
-                                                               kFolds=FakeKfold(),
-                                                               randomState="try",
-                                                               hyperParamSearch="try",
-                                                               metrics="try",
-                                                               argumentDictionaries={
-                                                                   "Monoview": [
+                                                      args=FakeArg(),
+                                                      kFolds=FakeKfold(),
+                                                      randomState="try",
+                                                      hyperParamSearch="try",
+                                                      metrics="try",
+                                                      argumentDictionaries={
+                                                                   "monoview": [
                                                                        {
                                                                            "try": 0},
                                                                        {
                                                                            "try2": 100}]},
-                                                               benchmark="try",
-                                                               views="try",
-                                                               viewsIndices="try",
-                                                               flag=None,
-                                                               labels=np.array(
+                                                      benchmark="try",
+                                                      views="try",
+                                                      viewsIndices="try",
+                                                      flag=None,
+                                                      labels=np.array(
                                                                    [0, 1, 2, 1,
                                                                     2, 2, 2, 12,
                                                                     1, 2, 1, 1,
                                                                     2, 1, 21]),
-                                                               ExecMonoview_multicore=fakeExecMono,
-                                                               ExecMultiview_multicore=fakeExecMulti,
-                                                               initMultiviewArguments=fakeInitMulti)
+                                                      ExecMonoview_multicore=fakeExecMono,
+                                                      ExecMultiview_multicore=fakeExecMulti,
+                                                      initMultiviewArguments=fakeInitMulti)
 
         cls.assertEqual(flag, None)
         cls.assertEqual(results ,
@@ -208,34 +208,34 @@ class Test_execOneBenchmark(unittest.TestCase):
 
     @classmethod
     def tearDownClass(cls):
-        os.remove("multiview_platform/Tests/tmp_tests/train_indices.csv")
-        os.remove("multiview_platform/Tests/tmp_tests/train_labels.csv")
+        os.remove("multiview_platform/tests/tmp_tests/train_indices.csv")
+        os.remove("multiview_platform/tests/tmp_tests/train_labels.csv")
         os.remove(
-            "multiview_platform/Tests/tmp_tests/folds/test_labels_fold_0.csv")
+            "multiview_platform/tests/tmp_tests/folds/test_labels_fold_0.csv")
         os.remove(
-            "multiview_platform/Tests/tmp_tests/folds/test_labels_fold_1.csv")
-        os.rmdir("multiview_platform/Tests/tmp_tests/folds")
-        os.rmdir("multiview_platform/Tests/tmp_tests")
+            "multiview_platform/tests/tmp_tests/folds/test_labels_fold_1.csv")
+        os.rmdir("multiview_platform/tests/tmp_tests/folds")
+        os.rmdir("multiview_platform/tests/tmp_tests")
 
 
 class Test_execOneBenchmark_multicore(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        os.mkdir("multiview_platform/Tests/tmp_tests")
+        os.mkdir("multiview_platform/tests/tmp_tests")
 
     def test_simple(cls):
-        flag, results = ExecClassif.execOneBenchmark_multicore(
+        flag, results = exec_classif.execOneBenchmark_multicore(
             nbCores=2,
             LABELS_DICTIONARY={0: "a", 1: "b"},
-            directory="multiview_platform/Tests/tmp_tests/",
+            directory="multiview_platform/tests/tmp_tests/",
             classificationIndices=([1, 2, 3, 4], [0, 10, 20, 30, 40]),
             args=FakeArg(),
             kFolds=FakeKfold(),
             randomState="try",
             hyperParamSearch="try",
             metrics="try",
-            argumentDictionaries={"Monoview": [{"try": 0}, {"try2": 100}]},
+            argumentDictionaries={"monoview": [{"try": 0}, {"try2": 100}]},
             benchmark="try",
             views="try",
             viewsIndices="try",
@@ -252,14 +252,14 @@ class Test_execOneBenchmark_multicore(unittest.TestCase):
 
     @classmethod
     def tearDownClass(cls):
-        os.remove("multiview_platform/Tests/tmp_tests/train_indices.csv")
-        os.remove("multiview_platform/Tests/tmp_tests/train_labels.csv")
+        os.remove("multiview_platform/tests/tmp_tests/train_indices.csv")
+        os.remove("multiview_platform/tests/tmp_tests/train_labels.csv")
         os.remove(
-            "multiview_platform/Tests/tmp_tests/folds/test_labels_fold_0.csv")
+            "multiview_platform/tests/tmp_tests/folds/test_labels_fold_0.csv")
         os.remove(
-            "multiview_platform/Tests/tmp_tests/folds/test_labels_fold_1.csv")
-        os.rmdir("multiview_platform/Tests/tmp_tests/folds")
-        os.rmdir("multiview_platform/Tests/tmp_tests")
+            "multiview_platform/tests/tmp_tests/folds/test_labels_fold_1.csv")
+        os.rmdir("multiview_platform/tests/tmp_tests/folds")
+        os.rmdir("multiview_platform/tests/tmp_tests")
 
 #
 # class Test_analyzeMulticlass(unittest.TestCase):
@@ -419,7 +419,7 @@ class Test_execOneBenchmark_multicore(unittest.TestCase):
 #                                 help='Classes used in the dataset (names of the folders) if not filled, random classes will be '
 #                                      'selected ex. walrus mole leopard', default=["yes", "no"])
 #         groupClass.add_argument('--CL_type', metavar='STRING', action='store', nargs="+",
-#                                 help='Determine whether to use Multiview and/or Monoview, or Benchmark',
+#                                 help='Determine whether to use multiview and/or monoview, or Benchmark',
 #                                 default=['Benchmark'])
 #         groupClass.add_argument('--CL_algos_monoview', metavar='STRING', action='store', nargs="+",
 #                                 help='Determine which monoview classifier to use if empty, considering all',
@@ -523,11 +523,11 @@ class Test_execOneBenchmark_multicore(unittest.TestCase):
 #                                 default=False)
 #
 #
-#         groupFusion = parser.add_argument_group('Fusion arguments')
+#         groupFusion = parser.add_argument_group('fusion arguments')
 #         groupFusion.add_argument('--FU_types', metavar='STRING', action='store', nargs="+",
 #                                  help='Determine which type of fusion to use',
 #                                  default=[''])
-#         groupEarlyFusion = parser.add_argument_group('Early Fusion arguments')
+#         groupEarlyFusion = parser.add_argument_group('Early fusion arguments')
 #         groupEarlyFusion.add_argument('--FU_early_methods', metavar='STRING', action='store', nargs="+",
 #                                       help='Determine which early fusion method of fusion to use',
 #                                       default=[''])
@@ -542,7 +542,7 @@ class Test_execOneBenchmark_multicore(unittest.TestCase):
 #         groupEarlyFusion.add_argument('--FU_E_cl_names', metavar='STRING', action='store', nargs='+',
 #                                       help='Name of the classifiers used for each early fusion method', default=[''])
 #
-#         groupLateFusion = parser.add_argument_group('Late Early Fusion arguments')
+#         groupLateFusion = parser.add_argument_group('Late Early fusion arguments')
 #         groupLateFusion.add_argument('--FU_late_methods', metavar='STRING', action='store', nargs="+",
 #                                      help='Determine which late fusion method of fusion to use',
 #                                      default=[''])
diff --git a/multiview_platform/Tests/test_ResultAnalysis.py b/multiview_platform/tests/test_ResultAnalysis.py
similarity index 97%
rename from multiview_platform/Tests/test_ResultAnalysis.py
rename to multiview_platform/tests/test_ResultAnalysis.py
index e74405d2c047515fdc76bd48803a8620f7a40b01..be59cce4c0d7c5186e3e0e06d4d36f62bf6564a3 100644
--- a/multiview_platform/Tests/test_ResultAnalysis.py
+++ b/multiview_platform/tests/test_ResultAnalysis.py
@@ -1,7 +1,7 @@
 # import unittest
 # import numpy as np
 #
-# from ..MonoMultiViewClassifiers import ResultAnalysis
+# from ..mono_multi_view_classifiers import ResultAnalysis
 #
 #
 # class Test_getMetricsScoresBiclass(unittest.TestCase):
diff --git a/multiview_platform/Versions.py b/multiview_platform/versions.py
similarity index 100%
rename from multiview_platform/Versions.py
rename to multiview_platform/versions.py
diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/2019_09_12-12_15-MonoviewMultiview--Plausible-LOG.log b/results/Plausible/n_0/started_2019_09_12-12_15_/2019_09_12-12_15-MonoviewMultiview--Plausible-LOG.log
new file mode 100644
index 0000000000000000000000000000000000000000..cebcc1af0b4e0865045497a66299c23427e2a3fa
--- /dev/null
+++ b/results/Plausible/n_0/started_2019_09_12-12_15_/2019_09_12-12_15-MonoviewMultiview--Plausible-LOG.log
@@ -0,0 +1,4 @@
+2019-09-12 12:15:46,117 DEBUG: Info:	 Enough copies of the dataset are already available
+2019-09-12 12:15:46,121 DEBUG: Start:	 Initializing Monoview classifiers arguments
+2019-09-12 12:15:46,121 DEBUG: Done:	 Initializing Monoview classifiers arguments
+2019-09-12 12:15:46,122 DEBUG: Start:	 Executing all the needed biclass benchmarks
diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_0.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_0.csv
new file mode 100644
index 0000000000000000000000000000000000000000..56a489f43d893f1fa11149aa5fc3e568f1546c18
--- /dev/null
+++ b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_0.csv
@@ -0,0 +1,160 @@
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_2.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_2.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_3.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_3.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_4.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/folds/test_labels_fold_4.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/train_labels.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/train_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11811f56387699cf03f36398c2729f636877217d
--- /dev/null
+++ b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_1/No-vs-Yes/train_labels.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_0.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_0.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b8361c36673a372de09060e2a5af796ebf9e7824
--- /dev/null
+++ b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_0.csv
@@ -0,0 +1,160 @@
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_1.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_1.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_2.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_2.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_3.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_3.csv
new file mode 100644
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_4.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/folds/test_labels_fold_4.csv
new file mode 100644
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/train_indices.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/train_indices.csv
new file mode 100644
index 0000000000000000000000000000000000000000..11dcd77f87dde58d38349595e4e9fd091e1003b2
--- /dev/null
+++ b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/train_indices.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/train_labels.csv b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/train_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c34a0292ea1257648a8acbaec49a637d8095ada2
--- /dev/null
+++ b/results/Plausible/n_0/started_2019_09_12-12_15_/iter_2/No-vs-Yes/train_labels.csv
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diff --git a/results/Plausible/n_0/started_2019_09_12-12_15_/randomState.pickle b/results/Plausible/n_0/started_2019_09_12-12_15_/randomState.pickle
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diff --git a/results/Plausible/started_2019_09_12-11_15_/2019_09_12-11_15-MonoviewMultiview--Plausible-LOG.log b/results/Plausible/started_2019_09_12-11_15_/2019_09_12-11_15-MonoviewMultiview--Plausible-LOG.log
new file mode 100644
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--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/2019_09_12-11_15-MonoviewMultiview--Plausible-LOG.log
@@ -0,0 +1,7 @@
+2019-09-12 11:15:36,540 DEBUG: Start:	 Creating 2 temporary datasets for multiprocessing
+2019-09-12 11:15:36,540 WARNING:  WARNING : /!\ This may use a lot of HDD storage space : 1.82578125e-05 Gbytes /!\ 
+2019-09-12 11:15:36,541 WARNING: You have 15 seconds to stop the dataset copy by typing n
+2019-09-12 11:15:51,552 DEBUG: Start:	 Creating datasets for multiprocessing
+2019-09-12 11:15:51,556 DEBUG: Start:	 Initializing Monoview classifiers arguments
+2019-09-12 11:15:51,557 DEBUG: Done:	 Initializing Monoview classifiers arguments
+2019-09-12 11:15:51,570 DEBUG: Start:	 Executing all the needed biclass benchmarks
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-full_pred.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-full_pred.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-metrics.png b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-metrics.png
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4217aa954dccf953da2799998ddc205deeec3c2a
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+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
@@ -0,0 +1,192 @@
+Classification on Plausible database for ViewNumber0 with Adaboost.
+
+f1_score on train : 0.8799999999999999
+f1_score on test : 0.8571428571428571
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- Adaboostwith n_estimators : 133, base_estimator : DecisionTreeClassifier
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.14285714285714285
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9166666666666666
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8461538461538461
+		- Score on test : 0.75
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.1428571428571429
+
+
+ Classification took 0:00:09
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 7, feature importance : 0.4512313405765816
+- Feature index : 2, feature importance : 0.14178323550020988
+- Feature index : 4, feature importance : 0.098936521213332
+- Feature index : 6, feature importance : 0.09639978807241292
+- Feature index : 9, feature importance : 0.08295676759522444
+- Feature index : 1, feature importance : 0.05046178939750596
+- Feature index : 3, feature importance : 0.04117978545910412
+- Feature index : 5, feature importance : 0.037050772185629036
+
+
+ Estimator error | Estimator weight
+0.14814814814814817 | 0.10308236152142845
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\ No newline at end of file
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7a514b27de9c230179d07e86174fc0ad8093c356
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4c257cc4ca8e25fb9015ef73d8a6684c903c210e
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b000f9822dc214521c39f40cf87920c631f9f0e0
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
@@ -0,0 +1,47 @@
+Classification on Plausible database for ViewNumber0 with AdaboostGraalpy.
+
+f1_score on train : 0.8799999999999999
+f1_score on test : 0.8571428571428571
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostGraalpywith n_iterations : 330, n_stumps : 1, random_state : None
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.14285714285714285
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9166666666666666
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8461538461538461
+		- Score on test : 0.75
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.1428571428571429
+
+
+ Classification took 0:00:02
+
+ Classifier Interpretation : 
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7a514b27de9c230179d07e86174fc0ad8093c356
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fea2911a670e11052a800e12f55089ce9426cd6d
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_metrics.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_metrics.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d362abfc4b715ef275c1daed84c3f7c74d0b7fad
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_16_02-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_metrics.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-full_pred.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-full_pred.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
new file mode 100644
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+Classification on Plausible database for ViewNumber0 with AdaboostPregen.
+
+f1_score on train : 0.8799999999999999
+f1_score on test : 0.8571428571428571
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostPregenwith n_estimators : 130, base_estimator : DecisionTreeClassifier, n_stumps : 1, random_state : <mtrand.RandomState object at 0x7fc8ceb8ca68>
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.14285714285714285
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9166666666666666
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8461538461538461
+		- Score on test : 0.75
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.1428571428571429
+
+
+ Classification took 0:00:15
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 7, feature importance : 0.3013127912156881
+- Feature index : 17, feature importance : 0.15151455245406334
+- Feature index : 2, feature importance : 0.09896909766512689
+- Feature index : 19, feature importance : 0.06305256140479262
+- Feature index : 14, feature importance : 0.051780205671756584
+- Feature index : 16, feature importance : 0.05100864156571934
+- Feature index : 4, feature importance : 0.048427791586712815
+- Feature index : 6, feature importance : 0.04663002189656192
+- Feature index : 12, feature importance : 0.040279845407527215
+- Feature index : 11, feature importance : 0.031614704971605824
+- Feature index : 5, feature importance : 0.027590872063692262
+- Feature index : 9, feature importance : 0.02097031950719099
+- Feature index : 13, feature importance : 0.02069167788784662
+- Feature index : 1, feature importance : 0.019495590716871788
+- Feature index : 3, feature importance : 0.016835249803455413
+- Feature index : 15, feature importance : 0.009826076181388222
+
+
+ Estimator error | Estimator weight
+0.14814814814814817 | 0.10440711755432026
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\ No newline at end of file
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7a514b27de9c230179d07e86174fc0ad8093c356
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen/ViewNumber0/2019_09_12-11_16_04-Results-AdaboostPregen-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cebf023a621fe2375e36e400d517921760d6cd73
--- /dev/null
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
new file mode 100644
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--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
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+Classification on Plausible database for ViewNumber0 with AdaboostPregen10.
+
+f1_score on train : 0.8799999999999999
+f1_score on test : 0.8571428571428571
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostPregen10with n_estimators : 100, base_estimator : DecisionTreeClassifier, n_stumps : 10, random_state : <mtrand.RandomState object at 0x7fc8ceb8ca68>
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 0.8571428571428571
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.14285714285714285
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9166666666666666
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8461538461538461
+		- Score on test : 0.75
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.1428571428571429
+
+
+ Classification took 0:00:24
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 71, feature importance : 0.12689592591079354
+- Feature index : 126, feature importance : 0.05697790824543862
+- Feature index : 175, feature importance : 0.047272519602349745
+- Feature index : 174, feature importance : 0.0420779015106621
+- Feature index : 176, feature importance : 0.041214317830667424
+- Feature index : 68, feature importance : 0.040361791836590756
+- Feature index : 177, feature importance : 0.03832739594378058
+- Feature index : 149, feature importance : 0.028775021063197577
+- Feature index : 173, feature importance : 0.02678647306546427
+- Feature index : 162, feature importance : 0.024975994946198635
+- Feature index : 140, feature importance : 0.02316442062959914
+- Feature index : 95, feature importance : 0.0211008382975498
+- Feature index : 75, feature importance : 0.01990738505808622
+- Feature index : 77, feature importance : 0.019793506267758835
+- Feature index : 132, feature importance : 0.019556293178168014
+- Feature index : 171, feature importance : 0.01913273084140539
+- Feature index : 120, feature importance : 0.018262981426596433
+- Feature index : 72, feature importance : 0.01753853472450508
+- Feature index : 125, feature importance : 0.016610526976555566
+- Feature index : 128, feature importance : 0.015745464452194154
+- Feature index : 179, feature importance : 0.014745178472067385
+- Feature index : 143, feature importance : 0.014739389381663647
+- Feature index : 165, feature importance : 0.013834826601869256
+- Feature index : 172, feature importance : 0.013570276619927282
+- Feature index : 190, feature importance : 0.013452314707375868
+- Feature index : 196, feature importance : 0.012841680486824408
+- Feature index : 166, feature importance : 0.012220694008748909
+- Feature index : 142, feature importance : 0.011411357440130334
+- Feature index : 198, feature importance : 0.010728371397906743
+- Feature index : 48, feature importance : 0.00953857443636483
+- Feature index : 113, feature importance : 0.009344725319043404
+- Feature index : 167, feature importance : 0.008960456108215888
+- Feature index : 124, feature importance : 0.008878540006729172
+- Feature index : 44, feature importance : 0.00874070308243857
+- Feature index : 70, feature importance : 0.008414662431837293
+- Feature index : 194, feature importance : 0.008245344094056974
+- Feature index : 115, feature importance : 0.008132439244978832
+- Feature index : 199, feature importance : 0.007994156415171616
+- Feature index : 148, feature importance : 0.007953182611648244
+- Feature index : 121, feature importance : 0.007872607785374876
+- Feature index : 26, feature importance : 0.007820485338920697
+- Feature index : 11, feature importance : 0.007290687118183025
+- Feature index : 136, feature importance : 0.007267663525866059
+- Feature index : 58, feature importance : 0.007229926189861582
+- Feature index : 90, feature importance : 0.0072217059277589505
+- Feature index : 110, feature importance : 0.007029278509028481
+- Feature index : 27, feature importance : 0.006980516407321124
+- Feature index : 170, feature importance : 0.006863092996914979
+- Feature index : 152, feature importance : 0.00671377978322433
+- Feature index : 57, feature importance : 0.006614056717217335
+
+
+ Estimator error | Estimator weight
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+0.4588457206829805 | 0.011411357440130334
+0.45965524786415995 | 0.01118590005846274
+0.45109503710047066 | 0.013573202283617188
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+0.4590965616419291 | 0.011341490561849018
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+0.46129870021191544 | 0.010728371397906743
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\ No newline at end of file
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7a514b27de9c230179d07e86174fc0ad8093c356
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv
new file mode 100644
index 0000000000000000000000000000000000000000..1686f7afd029f60060614f81df76da8850416c6f
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_20-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-metrics.png b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-metrics.png
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
new file mode 100644
index 0000000000000000000000000000000000000000..58efd685fa45035825f46e3069b69097448e4528
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
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+Classification on Plausible database for ViewNumber0 with AdaboostPregenTree.
+
+f1_score on train : 0.8799999999999999
+f1_score on test : 1.0
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostPregenTreewith n_estimators : 147, base_estimator : DecisionTreeClassifier, n_stumps : 100, random_state : <mtrand.RandomState object at 0x7fc8ceb8ca68>, max_depth : 3
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 1.0
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 1.0
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.8799999999999999
+		- Score on test : 1.0
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.0
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 1.0
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9166666666666666
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8461538461538461
+		- Score on test : 1.0
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.0
+
+
+ Classification took 0:00:19
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 59, feature importance : 0.250995564710809
+- Feature index : 11, feature importance : 0.228370478207426
+- Feature index : 67, feature importance : 0.13255801862890249
+- Feature index : 93, feature importance : 0.0817974084494998
+- Feature index : 15, feature importance : 0.07605852141818412
+- Feature index : 46, feature importance : 0.07536561352287406
+- Feature index : 94, feature importance : 0.03234258235224861
+- Feature index : 20, feature importance : 0.03172375706632357
+- Feature index : 12, feature importance : 0.02471893984511931
+- Feature index : 91, feature importance : 0.02093525976545977
+- Feature index : 88, feature importance : 0.016317621688246974
+- Feature index : 69, feature importance : 0.015121931690447439
+- Feature index : 19, feature importance : 0.013694302654458765
+
+
+ Estimator error | Estimator weight
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\ No newline at end of file
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..7a514b27de9c230179d07e86174fc0ad8093c356
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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new file mode 100644
index 0000000000000000000000000000000000000000..f3e434c4ed76992a31ab1a808534b1029c123b31
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.png b/results/Plausible/started_2019_09_12-11_15_/iter_1/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_45-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_metrics.png
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@@ -0,0 +1,93 @@
+Classification on Plausible database for ViewNumber0 with Adaboost.
+
+f1_score on train : 0.888888888888889
+f1_score on test : 0.5
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- Adaboostwith n_estimators : 36, base_estimator : DecisionTreeClassifier
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.2857142857142857
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9230769230769231
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8571428571428571
+		- Score on test : 0.3333333333333333
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.2857142857142857
+
+
+ Classification took 0:00:05
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 4, feature importance : 0.27658467471101356
+- Feature index : 8, feature importance : 0.19573951165821046
+- Feature index : 6, feature importance : 0.18280731014638574
+- Feature index : 5, feature importance : 0.16903462489495508
+- Feature index : 9, feature importance : 0.14798281912021868
+- Feature index : 1, feature importance : 0.027851059469216524
+
+
+ Estimator error | Estimator weight
+0.14814814814814817 | 0.19200155659818333
+0.38586956521739135 | 0.051008835793725844
+0.3936806680792721 | 0.047404005435788536
+0.37228903278857023 | 0.05734244574929592
+0.398272474209923 | 0.04529669094594151
+0.4118750833258546 | 0.03910053641510028
+0.4250797626697292 | 0.033144143615527484
+0.4283316881714667 | 0.03168498826471951
+0.43731652573211927 | 0.02766745835615383
+0.44309561858440544 | 0.025093236538203483
+0.43079080779356566 | 0.030583418971653616
+0.4598352346382873 | 0.01767287917602858
+0.4403809987263011 | 0.026301530454305708
+0.44683031587002653 | 0.023433355212912888
+0.4504914402320589 | 0.021808761265694858
+0.44948714351124863 | 0.022254165345780143
+0.4510907159641257 | 0.02154306884423793
+0.45544866387004146 | 0.01961278848073342
+0.4579218975766406 | 0.01851867364299663
+0.457682022079224 | 0.01862474927377489
+0.4589126743991415 | 0.018080631875525676
+0.46192784192550773 | 0.016748436070227
+0.46368051891303597 | 0.01597461997086425
+0.46341663977769615 | 0.016091098190955406
+0.4644191927879085 | 0.015648611335983997
+0.46679482207116896 | 0.014600603425010093
+0.4665083844499344 | 0.014726929101138075
+0.46861092604470134 | 0.013799880333150077
+0.46781076921909037 | 0.014152624288467577
+0.46770812250454086 | 0.014197880671655722
+0.46966713295776846 | 0.013334366998891612
+0.4713388374510811 | 0.012597821908079565
+0.47014423017452733 | 0.013124130368078453
+0.4718265124910249 | 0.012383008695365834
+0.4722283267600983 | 0.012206033622317026
+0.4721602079158782 | 0.012236034763531318
\ No newline at end of file
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/Adaboost/ViewNumber0/2019_09_12-11_15_52-Results-Adaboost-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e69d38d03f0d60f7c1713048ac1f7bfdc0f836da
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
@@ -0,0 +1,47 @@
+Classification on Plausible database for ViewNumber0 with AdaboostGraalpy.
+
+f1_score on train : 0.888888888888889
+f1_score on test : 0.5
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostGraalpywith n_iterations : 211, n_stumps : 1, random_state : None
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.2857142857142857
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9230769230769231
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8571428571428571
+		- Score on test : 0.3333333333333333
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.2857142857142857
+
+
+ Classification took 0:00:02
+
+ Classifier Interpretation : 
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bf23f59b2f25f54da7318c138a84933d02ed6090
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cfdea50064ce593ccd080071d75e8263a1f1f5ce
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_labels.csv
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_metrics.csv b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostGraalpy/ViewNumber0/2019_09_12-11_15_58-Results-AdaboostGraalpy-No-Yes-learnRate_0.79-Plausible-ViewNumber0-train_metrics.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ec198c03cdc1fb6b2ec02e7592f8aa2628d2efea
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+Classification on Plausible database for ViewNumber0 with AdaboostPregen.
+
+f1_score on train : 0.888888888888889
+f1_score on test : 0.8
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostPregenwith n_estimators : 7, base_estimator : DecisionTreeClassifier, n_stumps : 1, random_state : <mtrand.RandomState object at 0x7fc164e80a68>
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.8
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.8
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.14285714285714285
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.8571428571428571
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9230769230769231
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8571428571428571
+		- Score on test : 0.6666666666666666
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.1428571428571429
+
+
+ Classification took 0:00:13
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 4, feature importance : 0.4126419371335908
+- Feature index : 18, feature importance : 0.28273692167778064
+- Feature index : 16, feature importance : 0.12323805240541051
+- Feature index : 15, feature importance : 0.09734980605803975
+- Feature index : 19, feature importance : 0.08403328272517843
+
+
+ Estimator error | Estimator weight
+0.14814814814814817 | 0.4126419371335908
+0.38586956521739135 | 0.10962611546375052
+0.3936806680792721 | 0.10187876065948587
+0.37228903278857023 | 0.12323805240541051
+0.398272474209923 | 0.09734980605803975
+0.4118750833258546 | 0.08403328272517843
+0.4250797626697292 | 0.07123204555454422
\ No newline at end of file
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
new file mode 100644
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+++ b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
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+Classification on Plausible database for ViewNumber0 with AdaboostPregen10.
+
+f1_score on train : 0.888888888888889
+f1_score on test : 0.5
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostPregen10with n_estimators : 100, base_estimator : DecisionTreeClassifier, n_stumps : 10, random_state : <mtrand.RandomState object at 0x7fc164e80a68>
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.2857142857142857
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9230769230769231
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8571428571428571
+		- Score on test : 0.3333333333333333
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.2857142857142857
+
+
+ Classification took 0:00:09
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 48, feature importance : 0.11951094465712629
+- Feature index : 158, feature importance : 0.04131831253225961
+- Feature index : 169, feature importance : 0.035692678652550124
+- Feature index : 85, feature importance : 0.03175033713047559
+- Feature index : 153, feature importance : 0.028194825191550504
+- Feature index : 165, feature importance : 0.026111773064163533
+- Feature index : 59, feature importance : 0.024805283512208284
+- Feature index : 198, feature importance : 0.02433804249487639
+- Feature index : 92, feature importance : 0.02307788083905098
+- Feature index : 156, feature importance : 0.022657169011343892
+- Feature index : 182, feature importance : 0.022499144786975928
+- Feature index : 52, feature importance : 0.02063049895805183
+- Feature index : 65, feature importance : 0.020130894101068154
+- Feature index : 69, feature importance : 0.019722250934096946
+- Feature index : 195, feature importance : 0.018423613605495288
+- Feature index : 187, feature importance : 0.01822928626551477
+- Feature index : 146, feature importance : 0.017537774219031892
+- Feature index : 188, feature importance : 0.0172988293700977
+- Feature index : 189, feature importance : 0.017221548319660513
+- Feature index : 186, feature importance : 0.015809416556100176
+- Feature index : 117, feature importance : 0.014872719027438107
+- Feature index : 141, feature importance : 0.01458604017384155
+- Feature index : 56, feature importance : 0.01457318899844308
+- Feature index : 180, feature importance : 0.013852056046587454
+- Feature index : 140, feature importance : 0.013705951733730619
+- Feature index : 190, feature importance : 0.013484494327546769
+- Feature index : 197, feature importance : 0.012722391962292835
+- Feature index : 157, feature importance : 0.012207936853336081
+- Feature index : 143, feature importance : 0.011946974686369363
+- Feature index : 193, feature importance : 0.01152690749014737
+- Feature index : 61, feature importance : 0.011254249359883927
+- Feature index : 80, feature importance : 0.011152590717566715
+- Feature index : 11, feature importance : 0.010738382242526016
+- Feature index : 151, feature importance : 0.010425027024500984
+- Feature index : 40, feature importance : 0.010015868514004808
+- Feature index : 196, feature importance : 0.00994336690327981
+- Feature index : 93, feature importance : 0.008809269716661003
+- Feature index : 119, feature importance : 0.008169085948479102
+- Feature index : 87, feature importance : 0.007841486410486088
+- Feature index : 181, feature importance : 0.0077077764008845655
+- Feature index : 112, feature importance : 0.007622861153008415
+- Feature index : 144, feature importance : 0.007616292801768363
+- Feature index : 166, feature importance : 0.00759761865771017
+- Feature index : 77, feature importance : 0.00724676608748144
+- Feature index : 39, feature importance : 0.007208452043501114
+- Feature index : 19, feature importance : 0.006967924925463577
+- Feature index : 54, feature importance : 0.006895492422579612
+- Feature index : 55, feature importance : 0.006846939887390366
+- Feature index : 171, feature importance : 0.006657713075875128
+- Feature index : 134, feature importance : 0.006631526343122455
+
+
+ Estimator error | Estimator weight
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\ No newline at end of file
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bf23f59b2f25f54da7318c138a84933d02ed6090
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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new file mode 100644
index 0000000000000000000000000000000000000000..4cdbdeebe25285160c1b6a71a87f96482a3595d8
--- /dev/null
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diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-times.csv b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregen10/ViewNumber0/2019_09_12-11_16_14-Results-AdaboostPregen10-No-Yes-learnRate_0.79-Plausible-ViewNumber0-times.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e3bd957bc0ebc7dd217c494d0d02afa5e2fa746d
--- /dev/null
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+++ b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_25-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-summary.txt
@@ -0,0 +1,60 @@
+Classification on Plausible database for ViewNumber0 with AdaboostPregenTree.
+
+f1_score on train : 0.888888888888889
+f1_score on test : 0.5
+
+Database configuration : 
+	- Database name : Plausible
+	- View name : ViewNumber0	 View shape : (34, 10)
+	- Learning Rate : 0.7941176470588235
+	- Labels used : No, Yes
+	- Number of cross validation folds : 5
+
+Classifier configuration : 
+	- AdaboostPregenTreewith n_estimators : 6, base_estimator : DecisionTreeClassifier, n_stumps : 100, random_state : <mtrand.RandomState object at 0x7fc164e80a68>, max_depth : 3
+	- Executed on 1 core(s) 
+	- Got configuration using randomized search with 2 iterations 
+
+
+	For F1 score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Accuracy score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For F-beta score using None as sample_weights, None as labels, 1 as pos_label, binary as average, 1.0 as beta (higher is better) : 
+		- Score on train : 0.888888888888889
+		- Score on test : 0.5
+	For Hamming loss using None as classes (lower is better) : 
+		- Score on train : 0.1111111111111111
+		- Score on test : 0.2857142857142857
+	For Jaccard_similarity score using None as sample_weights (higher is better) : 
+		- Score on train : 0.8888888888888888
+		- Score on test : 0.7142857142857143
+	For Precision score using None as sample_weights, None as labels, 1 as pos_label, binary as average (higher is better) : 
+		- Score on train : 0.9230769230769231
+		- Score on test : 1.0
+	For Recall score using None as sample_weights, None as labels, 1 as pos_label, binaryas average (higher is better)  : 
+		- Score on train : 0.8571428571428571
+		- Score on test : 0.3333333333333333
+	For Zero_one loss using None as sample_weights (lower is better) : 
+		- Score on train : 0.11111111111111116
+		- Score on test : 0.2857142857142857
+
+
+ Classification took 0:00:13
+
+ Classifier Interpretation : 
+Feature importances : 
+- Feature index : 67, feature importance : 0.5218771254399434
+- Feature index : 77, feature importance : 0.28781583205099637
+- Feature index : 1, feature importance : 0.19030704250906033
+
+
+ Estimator error | Estimator weight
+0.11111111111111113 | 0.5218771254399434
+0.4166666666666665 | 0.0844443857250128
+0.3749999999999999 | 0.1282018286105333
+0.4000000000000001 | 0.10175951612217249
+0.41269841269841273 | 0.08854752638688786
+0.42567567567567555 | 0.07516961771545028
\ No newline at end of file
diff --git a/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_25-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_25-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
new file mode 100644
index 0000000000000000000000000000000000000000..bf23f59b2f25f54da7318c138a84933d02ed6090
--- /dev/null
+++ b/results/Plausible/started_2019_09_12-11_15_/iter_2/No-vs-Yes/AdaboostPregenTree/ViewNumber0/2019_09_12-11_16_25-Results-AdaboostPregenTree-No-Yes-learnRate_0.79-Plausible-ViewNumber0-test_labels.csv
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new file mode 100644
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--- /dev/null
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diff --git a/results/Plausible/started_2019_09_12-11_15_/randomState.pickle b/results/Plausible/started_2019_09_12-11_15_/randomState.pickle
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diff --git a/setup.py b/setup.py
index 8090e9971ce21b1055bb4f2604ce183109c7a9a5..c92aa05939321d4f459cfc5ba2cce082d853333f 100644
--- a/setup.py
+++ b/setup.py
@@ -90,5 +90,5 @@ setup(
     # Il y a encore une chiée de paramètres possibles, mais avec ça vous
     # couvrez 90% des besoins
     # ext_modules=cythonize(
-    #     "multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/_custom_criterion.pyx"),
+    #     "multiview_platform/mono_multi_view_classifiers/monoview/additions/_custom_criterion.pyx"),
 )