title: retrieve intermediate features from a pipeline in Scikit (Python)
body: <p>I am using a pipeline very similar to the one given <a href="http://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html#building-a-pipeline" rel="noreferrer">in this example</a> :</p>
  <pre><code>&gt;&gt;&gt; text_clf = Pipeline([('vect', CountVectorizer()),
  ...                      ('tfidf', TfidfTransformer()),
  ...                      ('clf', MultinomialNB()),
  ... ])
  </code></pre>
  <p>over which I use <code>GridSearchCV</code> to find the best estimators over a parameter grid.</p>
  <p>However, I would like to get the column names of my training set with the <code>get_feature_names()</code> method from <code>CountVectorizer()</code>. Is this possible without implementing <code>CountVectorizer()</code> outside the pipeline?</p>