title: How to limit the number of floating digits shown on confusion matrix plot
body: <p>I followed the example from this <a href="http://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html#sphx-glr-auto-examples-model-selection-plot-confusion-matrix-py" rel="nofollow noreferrer">link</a>. When printing out the confusion matrix on console, it shows 2 floating digits (probably because of <code>np.set_printoptions(precision=2)</code>), but the output on the plot shows more than 2 digits.</p>
  
  <pre><code>def plot_confusion_matrix(cm, classes,
                            normalize=False,
                            title='Confusion matrix',
                            cmap=plt.cm.Blues):
      """
      This function prints and plots the confusion matrix.
      Normalization can be applied by setting `normalize=True`.
      """
      plt.imshow(cm, interpolation='nearest', cmap=cmap)
      plt.title(title)
      plt.colorbar()
      tick_marks = np.arange(len(classes))
      plt.xticks(tick_marks, classes, rotation=45)
      plt.yticks(tick_marks, classes)
  
      if normalize:
          cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
          print("Normalized confusion matrix")
      else:
          print('Confusion matrix, without normalization')
  
      print(cm)
  
      thresh = cm.max() / 2.
      for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):
          plt.text(j, i, cm[i, j],
                   horizontalalignment="center",
                   color="white" if cm[i, j] &gt; thresh else "black")
  
      plt.tight_layout()
      plt.ylabel('True label')
      plt.xlabel('Predicted label')
  
  # Compute confusion matrix
  cnf_matrix = confusion_matrix(y_test, y_pred)
  np.set_printoptions(precision=2)
  
  # Plot non-normalized confusion matrix
  plt.figure()
  plot_confusion_matrix(cnf_matrix, classes=class_names,
                        title='Confusion matrix, without normalization')
  
  # Plot normalized confusion matrix
  plt.figure()
  plot_confusion_matrix(cnf_matrix, classes=class_names, normalize=True,
                        title='Normalized confusion matrix')
  
  plt.show()
  </code></pre>
  
  <p>The matrix output looks something like this: </p>
  
  <p><a href="https://i.stack.imgur.com/kDhRM.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/kDhRM.png" alt="enter image description here"></a></p>