'Update the classifier with new training data and re-trains the
classifier.
:param new_data: New data as a list of tuples of the form
``(text, label)``.'

def update(self, new_data, *args, **kwargs):

    self.train_set += new_data
    self.train_features = [(self.extract_features(d), c) for (d, c) in self.train_set]
    try:
        self.classifier = self.nltk_class.train(self.train_features, *args, **kwargs)
    except AttributeError:
        raise ValueError('NLTKClassifier    must    have    a    nltk_class    variable    that    is    not    None.')
    return True
