title: What's the difference between KFold and ShuffleSplit CV?
body: <p>It seems like KFold generates the same values every time the object is iterated over, while Shuffle Split generates different indices every time. Is this correct? If so, what are the uses for one over the other?</p>
  
  <pre><code>cv = cross_validation.KFold(10, n_folds=2,shuffle=True,random_state=None)
  cv2 = cross_validation.ShuffleSplit(10,n_iter=2,test_size=0.5)
  print(list(iter(cv)))
  print(list(iter(cv)))
  print(list(iter(cv2)))
  print(list(iter(cv2)))
  </code></pre>
  
  <p>Yields the following output:</p>
  
  <pre><code>[(array([1, 3, 5, 8, 9]), array([0, 2, 4, 6, 7])), (array([0, 2, 4, 6, 7]), array([1, 3, 5, 8, 9]))]                                     
  [(array([1, 3, 5, 8, 9]), array([0, 2, 4, 6, 7])), (array([0, 2, 4, 6, 7]), array([1, 3, 5, 8, 9]))]                                     
  [(array([4, 6, 3, 2, 7]), array([8, 1, 9, 0, 5])), (array([3, 6, 7, 0, 5]), array([9, 1, 8, 4, 2]))]                                     
  [(array([3, 0, 2, 1, 7]), array([5, 6, 9, 4, 8])), (array([0, 7, 1, 3, 8]), array([6, 2, 5, 4, 9]))]    
  </code></pre>