new_contents: from svm import SVMModel
  
  if __name__ == '__main__':
      features = [
         # 'refuting',
         'ngrams',
         # 'polarity',
         'named',
         # 'jaccard'
      ]
  
      model = SVMModel()
      train_data = model.get_data('data/train_bodies.csv', 'data/train_stances.csv')
      test_data = model.get_data('data/competition_test_bodies.csv', 'data/competition_test_stances.csv')
  
      X_test = test_data['X']
      X_train = train_data['X']
  
      Only_R_UR = True
      if Only_R_UR is True:
          y_test = model.related_unrelated(test_data['y'])
          y_train = model.related_unrelated(train_data['y'])
      else:
          y_test = test_data['y']
          y_train = train_data['y']
  
      classifier = model.get_trained_classifier(X_train, y_train)
      predicted = model.test_classifier(classifier, X_test, y_test)
  
      print str(model._use_features)
      print "Precision %f" % model.precision(y_test, predicted)
      print "Recal %f" % model.recal(y_test, predicted)
      print "Accuracy %f" % model.accuracy(y_test, predicted)
  
subject: Add svm experiment on test data