merge

config_files/config.yml

@@ -110,15 +110,6 @@ cb_boost:
   n_max_iterations: [10]
   n_stumps: [1]
 
-min_cq_graalpy:
-  mu: [0.01]
-  n_stumps_per_attribute: [1]
-
-min_cq_graalpy_tree:
-  mu: [0.01]
-  n_stumps_per_attribute: [1]
-  max_depth: [2]
-
 lasso:
   alpha: [1]
   max_iter: [2]
@@ -126,10 +117,6 @@ lasso:
 gradient_boosting:
   n_estimators: [2]
 
-min_cq:
-  mu: [0.01]
-  n_stumps_per_attribute: [1]
-
 
 ######################################
 # The Multiview Classifier arguments #

multiview_platform/mono_multi_view_classifiers/monoview/analyze_result.py

@@ -5,6 +5,21 @@ from .. import metrics
 
 def getDBConfigString(name, feat, classification_indices, shape,
                       classLabelsNames, KFolds):
+    """
+    
+    Parameters
+    ----------
+    name
+    feat
+    classification_indices
+    shape
+    classLabelsNames
+    KFolds
+
+    Returns
+    -------
+
+    """
     learningRate = float(len(classification_indices[0])) / (
                 len(classification_indices[0]) + len(classification_indices[1]))
     dbConfigString = "Database configuration : \n"

multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cb_boost.py

@@ -59,6 +59,7 @@ class CBBoost(CBBoostClassifier, BaseMonoviewClassifier):
         """
         return True
 
+
     def getInterpret(self, directory, y_test):
         """
         return interpretation string

multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cg_desc.py

@@ -45,7 +45,7 @@ class CGDesc(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
 
     def canProbas(self):
         """Used to know if the classifier can return label probabilities"""
-        return True
+        return False
 
     def getInterpret(self, directory, y_test):
         return self.getInterpretQar(directory, y_test)

multiview_platform/mono_multi_view_classifiers/monoview_classifiers/cq_boost.py

@@ -37,7 +37,7 @@ class CQBoost(ColumnGenerationClassifier, BaseMonoviewClassifier):
 
     def canProbas(self):
         """Used to know if the classifier can return label probabilities"""
-        return True
+        return False
 
     def getInterpret(self, directory, y_test):
         np.savetxt(directory + "train_metrics.csv", self.train_metrics,

multiview_platform/mono_multi_view_classifiers/monoview_classifiers/decision_tree_pregen.py

@@ -61,7 +61,7 @@ class DecisionTreePregen(DecisionTreeClassifier, BaseMonoviewClassifier,
 
     def canProbas(self):
         """Used to know if the classifier can return label probabilities"""
-        return True
+        return False
 
     def getInterpret(self, directory, y_test):
         interpretString = ""

multiview_platform/mono_multi_view_classifiers/monoview_classifiers/gradient_boosting.py

@@ -71,7 +71,7 @@ class GradientBoosting(GradientBoostingClassifier, BaseMonoviewClassifier):
 
     def canProbas(self):
         """Used to know if the classifier can return label probabilities"""
-        return True
+        return False
 
     def getInterpret(self, directory, y_test):
         interpretString = ""

multiview_platform/mono_multi_view_classifiers/monoview_classifiers/lasso.py

@@ -47,7 +47,6 @@ class Lasso(LassoSK, BaseMonoviewClassifier):
     """
     def __init__(self, random_state=None, alpha=1.0,
                  max_iter=10, warm_start=False, **kwargs):
-
         super(Lasso, self).__init__(
             alpha=alpha,
             max_iter=max_iter,