April 2018
Beginner
552 pages
13h 58m
English
import nltk.classify.utilfrom nltk.classify import NaiveBayesClassifierfrom nltk.corpus import movie_reviews
def collect_features(word_list): word = [] return dict ([(word, True) for word in word_list])
if __name__=='__main__': plus_filenum = movie_reviews.fileids('pos') minus_filenum = movie_reviews.fileids('neg')
feature_pluspts = [(collect_features(movie_reviews.words(fileids=[f])),'Positive') for f in plus_filenum] feature_minuspts = [(collect_features(movie_reviews.words(fileids=[f])),'Negative') for f in minus_filenum]