diff --git a/sklearn/preprocessing/label.py b/sklearn/preprocessing/label.py
index 7a391b3f60b19..52156b23e682b 100644
--- a/sklearn/preprocessing/label.py
+++ b/sklearn/preprocessing/label.py
@@ -732,7 +732,9 @@ def fit_transform(self, y):
         class_mapping = np.empty(len(tmp), dtype=dtype)
         class_mapping[:] = tmp
         self.classes_, inverse = np.unique(class_mapping, return_inverse=True)
-        yt.indices = np.take(inverse, yt.indices)
+        # ensure yt.indices keeps its current dtype
+        yt.indices = np.array(inverse[yt.indices], dtype=yt.indices.dtype,
+                              copy=False)
 
         if not self.sparse_output:
             yt = yt.toarray()
diff --git a/sklearn/preprocessing/tests/test_label.py b/sklearn/preprocessing/tests/test_label.py
index baf1cfbc8bddd..f48ad29bd29b5 100644
--- a/sklearn/preprocessing/tests/test_label.py
+++ b/sklearn/preprocessing/tests/test_label.py
@@ -226,6 +226,8 @@ def test_sparse_output_multilabel_binarizer():
             got = mlb.fit_transform(inp())
             assert_equal(issparse(got), sparse_output)
             if sparse_output:
+                # verify CSR assumption that indices and indptr have same dtype
+                assert_equal(got.indices.dtype, got.indptr.dtype)
                 got = got.toarray()
             assert_array_equal(indicator_mat, got)
             assert_array_equal([1, 2, 3], mlb.classes_)
@@ -236,6 +238,8 @@ def test_sparse_output_multilabel_binarizer():
             got = mlb.fit(inp()).transform(inp())
             assert_equal(issparse(got), sparse_output)
             if sparse_output:
+                # verify CSR assumption that indices and indptr have same dtype
+                assert_equal(got.indices.dtype, got.indptr.dtype)
                 got = got.toarray()
             assert_array_equal(indicator_mat, got)
             assert_array_equal([1, 2, 3], mlb.classes_)