title: mapping scikit-learn DecisionTreeClassifier.tree_.value to predicted class
body: <p>I am using a scikit-learn DecissionTreeClassifier on a 3 class dataset. After I fit the classifier I access all leaf nodes on the tree_ attribute in order to get the amount of instances that end up in a given node for each class.</p>
  
  <pre><code>clf = tree.DecisionTreeClassifier(max_depth=5)
  clf.fit(X, y)
  # lets assume there is a leaf node with id 5
  print clf.tree_.value[5]
  </code></pre>
  
  <p>This will print out:</p>
  
  <pre><code>&gt;&gt;&gt; array([[  0.,   1.,  68.]])
  </code></pre>
  
  <p>but ... how do I know which position in that array belongs to which class ?
  The classifier has a classes_ attribute which is also a list</p>
  
  <pre><code>&gt;&gt;&gt; clf.classes_
  array(['CLASS_1', 'CLASS_2', 'CLASS_3'], dtype=object)
  </code></pre>
  
  <p>Maybe index 1 on the value array matches the class on index 1 of the classes array and so on?</p>