ENH sparse matrix support in label binarization

Author: hamsal

doc/modules/preprocessing.rst

@@ -370,7 +370,7 @@ matrix from a list of multi-class labels::
 
     >>> lb = preprocessing.LabelBinarizer()
     >>> lb.fit([1, 2, 6, 4, 2])
-    LabelBinarizer(neg_label=0, pos_label=1)
+    LabelBinarizer(neg_label=0, pos_label=1, sparse_output=False)
     >>> lb.classes_
     array([1, 2, 4, 6])
     >>> lb.transform([1, 6])

sklearn/linear_model/ridge.py

@@ -571,7 +571,7 @@ def fit(self, X, y):
         """
         self._label_binarizer = LabelBinarizer(pos_label=1, neg_label=-1)
         Y = self._label_binarizer.fit_transform(y)
-        if not self._label_binarizer.multilabel_:
+        if not self._label_binarizer.y_type_.startswith('multilabel'):
             y = column_or_1d(y, warn=True)
 
         if self.class_weight: