title: sklearn log_loss different number of classes
body: <p>I'm using log_loss with sklearn</p>
  
  <pre><code>from sklearn.metrics import log_loss
  print log_loss(true, pred,normalize=False)
  </code></pre>
  
  <p>and i have following error:</p>
  
  <pre><code>ValueError: y_true and y_pred have different number of classes 38, 2
  </code></pre>
  
  <p>It is really strange to me since, the arrays look valid:</p>
  
  <pre><code>print pred.shape
  print np.unique(pred)
  print np.unique(pred).size
  (19191L,)
  [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
   25 26 27 28 29 30 31 32 33 34 35 36 37]
  38
  
  print true.shape
  print np.unique(true)
  print np.unique(true).size
  (19191L,)
  [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
   25 26 27 28 29 30 31 32 33 34 35 36 37]
  38
  </code></pre>
  
  <p>What is wrong with the log_loss? Why it throws the error?</p>
  
  <p>Sample data:</p>
  
  <pre><code>pred: array([ 0,  1,  2, ...,  3, 12, 16], dtype=int64)
  true: array([ 0,  1,  2, ...,  3, 12, 16])
  </code></pre>