title: How to transform new data using sklearn.pipeline
body: <p>I have created a pipeline with TfIdfVectorizer transformer and OnevsRestClassifier estimator and trained it on training data as follows</p>
  
  <pre><code># Split data using train_test_split
  print "Split data into train and test sets"
  x_train, x_test, y_train, y_test = train_test_split(
      data_x, data_y, test_size=0.33)
  
  # transform matrix of plots into lists to pass to a TfidfVectorizer
  train_x = [x[0].strip() for x in x_train.tolist()]
  test_x = [x[0].strip() for x in x_test.tolist()]
  
  # Pipeline fit and transform
  print "Learn the model using train data"
  model = text_clf.fit(train_x, y_train)
  
  # Predict the test data
  print "Predict the recipients on test data"
  predictions = model.predict(test_x)
  </code></pre>
  
  <p>Now, I want to use the trained model to predict classes for new unlabeled data.
  I tried this and got an error</p>
  
  <pre><code># Read text from input
  text = raw_input()
  print "Input : ", text
  new_data = text_clf.transform([text])
  predict = model.predict(new_data) 
  </code></pre>
  
  <p>This is the error. What Am I doing wrong?</p>
  
  <pre><code>AttributeError: 'OneVsRestClassifier' object has no attribute 'transform'
  </code></pre>