title: Is there an easy way to get confusion matrix for multiclass classification? (OneVsRest)
body: <p>I was using OneVsRest classifier on three class classification problem, (three random forests). Occurrence of each class is defined my dummy integer (1 for occurrence, 0 for otherwise). I was wondering if there is an easy alternative way to creating confusion matrix? As all approaches I came across, takes arguments in the form of y_pred, y_train = array, shape = [n_samples]. Ideally , I would like y_pred, y_train = array , shape = [n_samples, n_classes]</p>
  
  <p>SOME SAMPLE , SIMILAR TO THE STRUCTURE OF THE PROBLEM:</p>
  
  <pre><code>y_train = np.array([(1,0,0), (1,0,0), (0,0,1), (1,0,0), (0,1,0)])
  y_pred = np.array([(1,0,0), (0,1,0), (0,0,1), (0,1,0), (1,0,0)])
  
  
  print(metrics.confusion_matrix(y_train, y_pred) 
  </code></pre>
  
  <p>RETURNS:
      multilabel-indicator is not supported</p>