scikit-learn
diff --git a/‎sklearn/utils/validation.py
Lines changed: 16 additions & 12 deletions b/‎sklearn/utils/validation.py
Lines changed: 16 additions & 12 deletions
@@ -165,35 +165,35 @@ def _sparse_matrix_constructor(string_format):
         raise ValueError("Don't know how to construct a sparse matrix of type %s" % string_format)
 
 
-def _ensure_sparse_format(array, allowed_sparse, convert_sparse_to, dtype,
+def _ensure_sparse_format(spmatrix, allowed_sparse, convert_sparse_to, dtype,
                           order, copy, force_all_finite):
     if allowed_sparse is None:
         raise TypeError('A sparse matrix was passed, but dense '
                         'data is required. Use X.toarray() to '
                         'convert to a dense numpy array.')
-    sparse_type = _get_sparse_type_string(array)
+    sparse_type = _get_sparse_type_string(spmatrix)
     if sparse_type in allowed_sparse:
         # correct type
-        if dtype == array.dtype or dtype is None:
+        if dtype == spmatrix.dtype or dtype is None:
             # correct dtype
             if copy:
-                array = array.copy()
+                spmatrix = spmatrix.copy()
         else:
             # convert dtype
-            array = array.astype(dtype)
+            spmatrix = spmatrix.astype(dtype)
     else:
         # create new
-        array = _sparse_matrix_constructor(convert_sparse_to)(array, copy=copy,
-                                                              dtype=dtype)
+        spmatrix = _sparse_matrix_constructor(convert_sparse_to)(
+            spmatrix, copy=copy, dtype=dtype)
     if force_all_finite:
-        _assert_all_finite(array.data)
-    array.data = np.array(array.data, copy=False, order=order)
-    return array
+        _assert_all_finite(spmatrix.data)
+    spmatrix.data = np.array(spmatrix.data, copy=False, order=order)
+    return spmatrix
 
 
 def check_array(array, allowed_sparse=None, dtype=None, order=None, copy=False,
                 force_all_finite=True, convert_sparse_to=None, make_2d=True,
-                allow_nd=False):
+                allow_nd=True):
     """Check everything about an array"""
     if isinstance(allowed_sparse, str):
         allowed_sparse = [allowed_sparse]
@@ -292,7 +292,11 @@ def check_arrays(*arrays, **options):
 
     checked_arrays = []
     for array in arrays:
-        if (force_arrays or hasattr(array, "__array__") or hasattr(array, "shape")):
+        if array is None:
+            checked_arrays.append(array)
+            continue
+
+        if force_arrays or sp.issparse(array):
             array = check_array(array, allow_sparse, dtype, order, copy=copy,
                                 make_2d=False, allow_nd=allow_nd,
                                 force_all_finite=force_finite)