Valid

summit/multiview_platform/monoview_classifiers/adaboost_graalpy.py

@@ -11,10 +11,7 @@ from ..monoview.monoview_utils import CustomRandint, \
     BaseMonoviewClassifier, change_label_to_minus, change_label_to_zero
 
 classifier_class_name = "AdaboostGraalpy"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class AdaBoostGP(BaseEstimator, ClassifierMixin, BaseBoost):
     """Scikit-Learn compatible AdaBoost classifier. Original code by Pascal Germain, adapted by Jean-Francis Roy.

summit/multiview_platform/monoview_classifiers/adaboost_pregen.py

@@ -16,11 +16,7 @@ __status__ = "Prototype"  # Production, Development, Prototype
 
 
 classifier_class_name = "AdaboostPregen"
-<<<<<<< HEAD
-
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class AdaboostPregen(AdaBoostClassifier, BaseMonoviewClassifier,
                      PregenClassifier):

summit/multiview_platform/monoview_classifiers/additions/CBBoostUtils.py

@@ -316,19 +316,11 @@ class CBBoostClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
 
     def init_hypotheses(self, X, y):
         """Inintialization for the hyptotheses used to build the boosted vote"""
-<<<<<<< HEAD
-        if self.estimators_generator is "Stumps":
-            self.estimators_generator = StumpsClassifiersGenerator(
-                n_stumps_per_attribute=self.n_stumps,
-                self_complemented=self.self_complemented)
-        if self.estimators_generator is "Trees":
-=======
         if self.estimators_generator == "Stumps":
             self.estimators_generator = StumpsClassifiersGenerator(
                 n_stumps_per_attribute=self.n_stumps,
                 self_complemented=self.self_complemented)
         if self.estimators_generator == "Trees":
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
             self.estimators_generator = TreeClassifiersGenerator(
                 n_trees=self.n_stumps, max_depth=self.max_depth,
                 self_complemented=self.self_complemented)

summit/multiview_platform/monoview_classifiers/bagged_spkm.py

@@ -11,10 +11,7 @@ from ..utils.hyper_parameter_search import CustomRandint
 from ..monoview_classifiers.spkm import SPKM
 
 classifier_class_name = "BaggedSPKM"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class BaggedSPKM(BaseMonoviewClassifier, SPKMlikeSklearn):
 

summit/multiview_platform/monoview_classifiers/bagging.py

@@ -16,10 +16,7 @@ __status__ = "Prototype"  # Production, Development, Prototype
 
 
 classifier_class_name = "Bagging"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class Bagging(BaggingClassifier, BaseMonoviewClassifier,):
     """

summit/multiview_platform/monoview_classifiers/bagging_pregen.py

@@ -16,10 +16,7 @@ __status__ = "Prototype"  # Production, Development, Prototype
 
 
 classifier_class_name = "BaggingPregen"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class BaggingPregen(BaggingClassifier, BaseMonoviewClassifier,
                      PregenClassifier):

summit/multiview_platform/monoview_classifiers/cb_boost.py

@@ -77,16 +77,11 @@ class CBBoost(CBBoostClassifier, BaseMonoviewClassifier):
         -------
 
         """
-<<<<<<< HEAD
-        interpret_string = self.getInterpretCBBoost(directory, base_file_name, y_test)
-        interpret_string += self.get_feature_importance(directory, base_file_name)
-=======
         interpret_string = self.getInterpretCBBoost(directory, base_file_name,
                                                     y_test)
         interpret_string += self.get_feature_importance(directory,
                                                         base_file_name,
                                                         feature_ids)
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
         return interpret_string
 
     def get_name_for_fusion(self):

summit/multiview_platform/monoview_classifiers/cb_gradient_boost.py

@@ -23,10 +23,7 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "CBGradientBoosting"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 
 class CustomDecisionTreeGB(DecisionTreeClassifier):

summit/multiview_platform/monoview_classifiers/cg_desc.py

@@ -3,10 +3,7 @@ from ..monoview.monoview_utils import BaseMonoviewClassifier, CustomRandint
 
 
 classifier_class_name = "CGDesc"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class CGDesc(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
     """

summit/multiview_platform/monoview_classifiers/cq_boost.py

@@ -6,10 +6,7 @@ from ..monoview.monoview_utils import BaseMonoviewClassifier
 from ..utils.hyper_parameter_search import CustomRandint, CustomUniform
 
 classifier_class_name = "CQBoost"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class CQBoost(ColumnGenerationClassifier, BaseMonoviewClassifier):
 

summit/multiview_platform/monoview_classifiers/decision_tree_pregen.py

@@ -12,10 +12,7 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "DecisionTreePregen"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class DecisionTreePregen(DecisionTreeClassifier, BaseMonoviewClassifier,
                          PregenClassifier):

summit/multiview_platform/monoview_classifiers/gradient_boosting_pregen.py

@@ -17,10 +17,7 @@ __status__ = "Prototype"  # Production, Development, Prototype
 
 
 classifier_class_name = "GradientBoostingPregen"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class GradientBoostingPregen(GradientBoostingClassifier, BaseMonoviewClassifier,
                          PregenClassifier):

summit/multiview_platform/monoview_classifiers/hm_gb_cbound.py

@@ -7,10 +7,7 @@ import numpy.ma as ma
 import math
 
 classifier_class_name = "CBBoostGradientBoosting"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class CBBoostGradientBoosting(CBBoostClassifier, BaseMonoviewClassifier):
     """

summit/multiview_platform/monoview_classifiers/ib_random_forest.py

@@ -8,10 +8,7 @@ from ..utils.base import base_boosting_estimators
 from ..utils.hyper_parameter_search import CustomRandint, CustomUniform
 
 classifier_class_name = "IBRF"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class IBRF(BaseMonoviewClassifier, BalancedBaggingClassifier):
 

summit/multiview_platform/monoview_classifiers/ib_random_scm.py

@@ -8,10 +8,7 @@ from ..utils.base import base_boosting_estimators
 from ..utils.hyper_parameter_search import CustomRandint, CustomUniform
 
 classifier_class_name = "IBRSCM"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class IBRSCM(BaseMonoviewClassifier, BalancedBaggingClassifier):
 

summit/multiview_platform/monoview_classifiers/ib_scm.py

@@ -7,10 +7,7 @@ from ..utils.base import base_boosting_estimators
 from ..utils.hyper_parameter_search import CustomRandint, CustomUniform
 
 classifier_class_name = "IBSCM"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class IBSCM(BaseMonoviewClassifier, BalancedBaggingClassifier):
 

summit/multiview_platform/monoview_classifiers/imbalance_bagging.py

@@ -7,10 +7,7 @@ from ..utils.base import base_boosting_estimators
 from ..utils.hyper_parameter_search import CustomRandint, CustomUniform
 
 classifier_class_name = "ImbalanceBagging"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class ImbalanceBagging(BaseMonoviewClassifier, BalancedBaggingClassifier):
 

summit/multiview_platform/monoview_classifiers/min_cq.py

@@ -23,10 +23,7 @@ from .additions.BoostUtils import ConvexProgram as QP
 
 
 classifier_class_name = "MinCQ"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 # from majority_vote import MajorityVote
 # from voter import StumpsVotersGenerator, KernelVotersGenerator

summit/multiview_platform/monoview_classifiers/min_cq_graalpy.py

@@ -6,10 +6,7 @@ from ..monoview.monoview_utils import BaseMonoviewClassifier
 from ..utils.hyper_parameter_search import CustomRandint, CustomUniform
 
 classifier_class_name = "MinCQGraalpy"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class MinCQGraalpy(RegularizedBinaryMinCqClassifier, BaseMonoviewClassifier):
     """

summit/multiview_platform/monoview_classifiers/pregen_gradient_boost.py

@@ -17,10 +17,7 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "PGradientBoosting"
-<<<<<<< HEAD
-=======
 proto=True
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 
 class CustomDecisionTreeGB(DecisionTreeClassifier):
@@ -63,19 +60,11 @@ class PGradientBoosting(GradientBoostingClassifier, BaseMonoviewClassifier, Base
     def pregen_voters(self, X, y=None, generator="Stumps"):
         if y is not None:
             neg_y = change_label_to_minus(y)
-<<<<<<< HEAD
-            if generator is "Stumps":
-                self.estimators_generator = StumpsClassifiersGenerator(
-                    n_stumps_per_attribute=self.n_stumps,
-                    self_complemented=self.self_complemented)
-            elif generator is "Trees":
-=======
             if generator == "Stumps":
                 self.estimators_generator = StumpsClassifiersGenerator(
                     n_stumps_per_attribute=self.n_stumps,
                     self_complemented=self.self_complemented)
             elif generator == "Trees":
->>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
                 self.estimators_generator = TreeClassifiersGenerator(
                     n_trees=self.n_stumps, max_depth=self.max_depth_pregen)
             self.estimators_generator.fit(X, neg_y)