diff --git a/sklearn/base.py b/sklearn/base.py
index 8c3a9a8eba4da..f98f4bf7e8cc5 100644
--- a/sklearn/base.py
+++ b/sklearn/base.py
@@ -21,6 +21,18 @@ class ChangedBehaviorWarning(_ChangedBehaviorWarning):
 
 
 ##############################################################################
+def _first_and_last_element(arr):
+    """Returns first and last element of numpy array or sparse matrix."""
+    if isinstance(arr, np.ndarray) or hasattr(arr, 'data'):
+        # numpy array or sparse matrix with .data attribute
+        data = arr.data if sparse.issparse(arr) else arr
+        return data.flat[0], data.flat[-1]
+    else:
+        # Sparse matrices without .data attribute. Only dok_matrix at
+        # the time of writing, in this case indexing is fast
+        return arr[0, 0], arr[-1, -1]
+
+
 def clone(estimator, safe=True):
     """Constructs a new estimator with the same parameters.
 
@@ -73,9 +85,8 @@ def clone(estimator, safe=True):
                 equality_test = (
                     param1.shape == param2.shape
                     and param1.dtype == param2.dtype
-                    # We have to use '.flat' for 2D arrays
-                    and param1.flat[0] == param2.flat[0]
-                    and param1.flat[-1] == param2.flat[-1]
+                    and (_first_and_last_element(param1) ==
+                         _first_and_last_element(param2))
                 )
             else:
                 equality_test = np.all(param1 == param2)
@@ -92,8 +103,8 @@ def clone(estimator, safe=True):
             else:
                 equality_test = (
                     param1.__class__ == param2.__class__
-                    and param1.data[0] == param2.data[0]
-                    and param1.data[-1] == param2.data[-1]
+                    and (_first_and_last_element(param1) ==
+                         _first_and_last_element(param2))
                     and param1.nnz == param2.nnz
                     and param1.shape == param2.shape
                 )
diff --git a/sklearn/tests/test_base.py b/sklearn/tests/test_base.py
index 873808ff914af..6f4be0dcc8ab7 100644
--- a/sklearn/tests/test_base.py
+++ b/sklearn/tests/test_base.py
@@ -1,6 +1,8 @@
 # Author: Gael Varoquaux
 # License: BSD 3 clause
 
+import sys
+
 import numpy as np
 import scipy.sparse as sp
 
@@ -143,6 +145,24 @@ def test_clone_nan():
     assert_true(clf.empty is clf2.empty)
 
 
+def test_clone_sparse_matrices():
+    sparse_matrix_classes = [
+        getattr(sp, name)
+        for name in dir(sp) if name.endswith('_matrix')]
+
+    PY26 = sys.version_info[:2] == (2, 6)
+    if PY26:
+        # sp.dok_matrix can not be deepcopied in Python 2.6
+        sparse_matrix_classes.remove(sp.dok_matrix)
+
+    for cls in sparse_matrix_classes:
+        sparse_matrix = cls(np.eye(5))
+        clf = MyEstimator(empty=sparse_matrix)
+        clf_cloned = clone(clf)
+        assert_true(clf.empty.__class__ is clf_cloned.empty.__class__)
+        assert_array_equal(clf.empty.toarray(), clf_cloned.empty.toarray())
+
+
 def test_repr():
     # Smoke test the repr of the base estimator.
     my_estimator = MyEstimator()