Merged

summit/multiview_platform/monoview_classifiers/min_cq_graalpy.py

@@ -6,6 +6,10 @@ 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

@@ -17,6 +17,10 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "PGradientBoosting"
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 
 class CustomDecisionTreeGB(DecisionTreeClassifier):
@@ -59,11 +63,19 @@ 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)

summit/multiview_platform/monoview_classifiers/random_forest_pregen.py

@@ -17,6 +17,10 @@ __status__ = "Prototype"  # Production, Development, Prototype
 
 
 classifier_class_name = "RandomForestPregen"
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class RandomForestPregen(RandomForestClassifier, BaseMonoviewClassifier,
                     PregenClassifier):

summit/multiview_platform/monoview_classifiers/scm_mazid.py

@@ -9,6 +9,10 @@ from ..monoview.monoview_utils import BaseMonoviewClassifier
 from ..utils.hyper_parameter_search import CustomUniform, CustomRandint
 
 classifier_class_name = 'DecisionStumpSCMNew'
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class DecisionStumpSCMNew(BaseMonoviewClassifier):
     """

summit/multiview_platform/monoview_classifiers/scm_pregen.py

@@ -12,6 +12,10 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "SCMPregen"
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class SCMPregen(BaseMonoviewClassifier, PregenClassifier, scm):
     """

summit/multiview_platform/monoview_classifiers/self_opt_cb.py

 from .additions.SelOptCB import SelfOptCBBoostClassifier
 
 classifier_class_name = "SelfOptCBBoostBaseStump"
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class SelfOptCBBoostBaseStump(SelfOptCBBoostClassifier):
     def __init__(self, n_max_iterations=10, random_state=42, twice_the_same=True,

summit/multiview_platform/monoview_classifiers/self_opt_cb_pseudo.py

 from .additions.SelOptCB import SelfOptCBBoostClassifier
 
 classifier_class_name = "SelfOptCBBoostBaseStump"
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class SelfOptCBBoostBaseStump(SelfOptCBBoostClassifier):
     def __init__(self, n_max_iterations=10, random_state=42, twice_the_same=True,

summit/multiview_platform/monoview_classifiers/self_opt_cb_root.py

 from .additions.SelOptCB import SelfOptCBBoostClassifier
 
 classifier_class_name = "SelfOptCBBoostBaseStump"
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class SelfOptCBBoostBaseStump(SelfOptCBBoostClassifier):
     def __init__(self, n_max_iterations=10, random_state=42, twice_the_same=True,

summit/multiview_platform/monoview_classifiers/sgd.py

@@ -8,6 +8,7 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "SGD"
+proto=True
 
 
 class SGD(SGDClassifier, BaseMonoviewClassifier):

summit/multiview_platform/monoview_classifiers/spkm.py

@@ -9,6 +9,10 @@ from ..utils.hyper_parameter_search import CustomRandint
 from ..utils.dataset import get_samples_views_indices
 
 classifier_class_name = "SPKM"
+<<<<<<< HEAD
+=======
+proto=True
+>>>>>>> 258ada8c7e5025f984b03343596557abe8d3f5a4
 
 class SPKM(BaseMonoviewClassifier, SPKMlikeSklearn):
 

summit/multiview_platform/monoview_classifiers/svm_linear.py

@@ -8,7 +8,7 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "SVMLinear"
-
+proto=True
 
 class SVMLinear(SVCClassifier, BaseMonoviewClassifier):
     """

summit/multiview_platform/monoview_classifiers/svm_poly.py

@@ -11,7 +11,7 @@ __author__ = "Baptiste Bauvin"
 __status__ = "Prototype"  # Production, Development, Prototype
 
 classifier_class_name = "SVMPoly"
-
+proto=True
 
 class SVMPoly(SVCClassifier, BaseMonoviewClassifier):
     """

summit/multiview_platform/multiview/multiview_utils.py

@@ -140,7 +140,9 @@ def get_available_monoview_classifiers(need_probas=False):
     available_classifiers = [module_name
                              for module_name in dir(monoview_classifiers)
                              if not (
-                                 module_name.startswith("__") or module_name == "additions")]
+                                 module_name.startswith("__") or
+                                 module_name == "additions" or
+                                 hasattr(getattr(monoview_classifiers, module_name), "proto"))]
     if need_probas:
         proba_classifiers = []
         for module_name in available_classifiers: