def update(self, new_data, *args, **kwargs):
self.train_set += new_data<EOL>self.train_features = [(self.extract_features(d), c)<EOL>for d, c in self.train_set]<EOL>try:<EOL><INDENT>self.classifier = self.nltk_class.train(self.train_features,<EOL>*args, **kwargs)<EOL><DEDENT>except AttributeError:  <EOL><INDENT>raise ValueError("<STR_LIT>"<EOL>"<STR_LIT>")<EOL><DEDENT>return True<EOL>
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)``.