title: Does scikit's cross_val_predict calculates tfidf anew for each fold?
body: <p>I have trained a classifier like that: </p>
  
  <pre><code>text_clf = Pipeline([('vect', CountVectorizer()),('tfidf', TfidfTransformer()),('clf', clf),])  
  
  y_predicted=cross_validation.cross_val_predict(text_clf, X, y, cv=3, n_jobs=3, verbose=2)
  </code></pre>
  
  <p>Since I am using a pipeline object with a tfidf-statistics I wanted to know if the tfidf values get calculated anew for each fold or they are calculated on the whole dataset and the same values are used for each fold.</p>