MAINT Remove redundant sample_weights check in DummyClassifier (#15510)

fbchow · salliewalecka · rth · commit 725ca8f32e18 · 2019-12-26T14:03:24.000+01:00
Co-authored-by: Sallie Walecka &lt;sallie.walecka@gmail.com&gt;
diff --git a/sklearn/dummy.py b/sklearn/dummy.py
@@ -156,7 +156,7 @@ def fit(self, X, y, sample_weight=None):
 
         self.n_outputs_ = y.shape[1]
 
-        check_consistent_length(X, y, sample_weight)
+        check_consistent_length(X, y)
 
         if sample_weight is not None:
             sample_weight = _check_sample_weight(sample_weight, X)
@@ -245,7 +245,7 @@ def predict(self, X):
                 classes_ = [np.array([c]) for c in constant]
 
             y = _random_choice_csc(n_samples, classes_, class_prob,
-                                  self.random_state)
+                                   self.random_state)
         else:
             if self._strategy in ("most_frequent", "prior"):
                 y = np.tile([classes_[k][class_prior_[k].argmax()] for
