title: How to get most informative features for scikit-learn classifier for different class?
body: <p>NLTK package provides a method <code>show_most_informative_features()</code> to find the most important features for both class, with output like: </p>
  
  <pre><code>   contains(outstanding) = True              pos : neg    =     11.1 : 1.0
          contains(seagal) = True              neg : pos    =      7.7 : 1.0
     contains(wonderfully) = True              pos : neg    =      6.8 : 1.0
           contains(damon) = True              pos : neg    =      5.9 : 1.0
          contains(wasted) = True              neg : pos    =      5.8 : 1.0
  </code></pre>
  
  <p>As answered in this question <a href="https://stackoverflow.com/questions/11116697/how-to-get-most-informative-features-for-scikit-learn-classifiers">How to get most informative features for scikit-learn classifiers?</a> , this can also work in scikit-learn. However, for binary classifier, the answer in that question only outputs the best feature itself. </p>
  
  <p>So my question is, how can I identify the feature's associated class, like the example above (outstanding is most informative in pos class, and seagal is most informative in negative class)?</p>
  
  <p>EDIT: actually what I want is a list of most informative words for each class. How can I do that? Thanks!</p>