sentiment_lr = Pipeline([ ('count_vect', CountVectorizer(min_df = 100, ngram_range = (1,1), stop_words = 'english')), ('lr', LogisticRegression())]) sentiment_lr.fit(dftrain.text, dftrain.polarity) 12/14/2019 073927 AM INFO: Cell raised uncaught exception: --------------------------------------------------------------------------- MemoryError Traceback (most recent call last) <ipython-input-6-708336cd9e69> in <module> 4 stop_words = 'english')), 5 ('lr', LogisticRegression())]) ----> 6 sentiment_lr.fit(dftrain.text, dftrain.polarity)