diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py
index 9ed01abea4c3ed4e045c27fbed5d097c8eaa40d5..964f92254908fc9fe76b8fcb33173d79eb82a9a5 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py
@@ -739,7 +739,7 @@ def getInterpretBase(classifier, directory, classifier_name, weights,
     interpretString += "\n \t It generated {} columns by attributes and used {} iterations to converge, and selected {} couple(s) of opposed voters".format(classifier.n_stumps,
         len(weights_sort), classifier.nb_opposed_voters)
     if max(weights) > 0.50:
-        interpretString += "\n \t The vote is useless in this context : voter n°{} is a dictator of weight > 0.50".format(classifier.chosen_columns_[np.argmax(np.array(weights))])
+        interpretString += "\n \t The vote is useless in this context : voter nb {} is a dictator of weight > 0.50".format(classifier.chosen_columns_[np.argmax(np.array(weights))])
     if len(weights_sort) == classifier.n_max_iterations or len(weights) == classifier.n_total_hypotheses_:
         if len(weights) == classifier.n_max_iterations:
             interpretString += ", and used all available iterations, "
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py
index e0ea8568b7b911c6e9ab8e79f8705fe4173c2173..09277d17ee7114bb687b9c862f5e53d72dbdf5b9 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py
@@ -81,6 +81,7 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
         self.n_max_iterations = params["n_max_iterations"]
         # self.n_stumps = params["n_stumps_per_attribute"]
         # self.use_r = params["use_r"]
+        return self
 
     def fit(self, X, y):
 
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/MonoviewUtils.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/MonoviewUtils.py
index 59260507b66a5e3d99ad152db30415bd6b8967e6..1e7fd8177ac2e8d6136fbfcfca9082706567c412 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/MonoviewUtils.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/MonoviewUtils.py
@@ -31,6 +31,7 @@ def randomizedSearch(X_train, y_train, randomState, outputFileName, classifierMo
             nIter = nb_possible_combinations
         randomSearch = RandomizedSearchCV(estimator, n_iter=nIter, param_distributions=params_dict, refit=True,
                                           n_jobs=nbCores, scoring=scorer, cv=KFolds, random_state=randomState)
+        print(estimator)
         detector = randomSearch.fit(X_train, y_train)
 
         bestParams = estimator.genBestParams(detector)