Pass sample_weight as kwarg in VotingClassifier

jschendel · jschendel · commit dac3723da589 · 2017-08-03T22:27:58.000-06:00
diff --git a/sklearn/ensemble/voting_classifier.py b/sklearn/ensemble/voting_classifier.py
@@ -23,10 +23,10 @@
 from ..utils.metaestimators import _BaseComposition
 
 
-def _parallel_fit_estimator(estimator, X, y, sample_weight):
+def _parallel_fit_estimator(estimator, X, y, sample_weight=None):
     """Private function used to fit an estimator within a job."""
     if sample_weight is not None:
-        estimator.fit(X, y, sample_weight)
+        estimator.fit(X, y, sample_weight=sample_weight)
     else:
         estimator.fit(X, y)
     return estimator
@@ -185,7 +185,7 @@ def fit(self, X, y, sample_weight=None):
 
         self.estimators_ = Parallel(n_jobs=self.n_jobs)(
                 delayed(_parallel_fit_estimator)(clone(clf), X, transformed_y,
-                                                 sample_weight)
+                                                 sample_weight=sample_weight)
                 for clf in clfs if clf is not None)
 
         return self
