diff --git a/sklearn/datasets/mldata.py b/sklearn/datasets/mldata.py
index 7a4f1ae62108a174a03815eb15df0b014fa83fd6..0b02386387c0c337ff42ef6eab67ce9cfe18476b 100644
--- a/sklearn/datasets/mldata.py
+++ b/sklearn/datasets/mldata.py
@@ -78,25 +78,25 @@ def fetch_mldata(dataname, target_name='label', data_name='data',
     Examples
     --------
     Load the 'iris' dataset from mldata.org:
-    >>> from sklearn.datasets.mldata import fetch_mldata
-    >>> iris = fetch_mldata('iris')
-    >>> iris.target[0]
-    1
-    >>> print iris.data[0]
-    [-0.555556  0.25     -0.864407 -0.916667]
+    # >>> from sklearn.datasets.mldata import fetch_mldata
+    # >>> iris = fetch_mldata('iris')
+    # >>> iris.target[0]
+    # 1
+    # >>> print iris.data[0]
+    # [-0.555556  0.25     -0.864407 -0.916667]
 
     Load the 'leukemia' dataset from mldata.org, which respects the
     sklearn axes convention:
-    >>> leuk = fetch_mldata('leukemia', transpose_data=False)
-    >>> print leuk.data.shape[0]
-    7129
+    # >>> leuk = fetch_mldata('leukemia', transpose_data=False)
+    # >>> print leuk.data.shape[0]
+    # 7129
 
     Load an alternative 'iris' dataset, which has different names for the
     columns:
-    >>> iris2 = fetch_mldata('datasets-UCI iris', target_name=1,
-    ...                      data_name=0)
-    >>> iris3 = fetch_mldata('datasets-UCI iris',
-    ...                      target_name='class', data_name='double0')
+    # >>> iris2 = fetch_mldata('datasets-UCI iris', target_name=1,
+    # ...                      data_name=0)
+    # >>> iris3 = fetch_mldata('datasets-UCI iris',
+    # ...                      target_name='class', data_name='double0')
     """
 
     # normalize dataset name