title: feature importance for each class in multiclass classification
body: <p>I built a decision tree and it also gives me the feature importance for my classification. But how can I tell my program to give me the feature importance for each of my classes? To give me the overall feature importance I have this code:</p>
  
  <pre class="lang-py prettyprint-override"><code>importances = tree.feature_importances_
  #std = np.std([tree.feature_importances_ for tree in forest.estimators_],
              # axis=0)
  indices = np.argsort(importances)[::-1]
  
  # Print the feature ranking
  print("Feature ranking:")
  
  for f in range(X.shape[1]):
      print("%d. feature %d (%f)" % (f + 1, indices[f], importances[indices[f]]))
  
  # Plot the feature importances of the forest
  plt.figure()
  plt.title("Feature importances")
  plt.bar(range(X.shape[1]), importances[indices],
         color="r", yerr=std[indices], align="center")
  plt.xticks(range(X.shape[1]), [feature_cols[i] for i in indices])
  plt.xlim([-1, X.shape[1]])
  plt.show()
  </code></pre>
  
  <p>I have four classes - 0, 1, 2, 3.
  Does someone know a solution?</p>