How to run this code （with no basic on using python）

[Zac]

import nltk.classify.util

from nltk.classify import NaiveBayesClassifier

from nltk.corpus import movie_reviews

 

def word_feats(words):

    return dict([(word, True) for word in words])

 

negids = movie_reviews.fileids('neg')

posids = movie_reviews.fileids('pos')

 

negfeats = [(word_feats(movie_reviews.words(fileids=[f])), 'neg') for f in negids]

posfeats = [(word_feats(movie_reviews.words(fileids=[f])), 'pos') for f in posids]

 

negcutoff = len(negfeats)*3/4

poscutoff = len(posfeats)*3/4

 

trainfeats = negfeats[:negcutoff] + posfeats[:poscutoff]

testfeats = negfeats[negcutoff:] + posfeats[poscutoff:]

print 'train on %d instances, test on %d instances' % (len(trainfeats), len(testfeats))

 

classifier = NaiveBayesClassifier.train(trainfeats)

print 'accuracy:', nltk.classify.util.accuracy(classifier, testfeats)

classifier.show_most_informative_features()

[Zac]

the code is from here:
http://streamhacker.com/2010/05/10/text-classification-sentiment-analysis-naive-bayes-classifier/#

[Alex Rudnick]

Hey Zac,

There are some really good resources out there for learning how to use
Python! I recommend Dive Into Python 3 and perhaps How To Think Like A
Computer Scientist, both of which are free online.

http://getpython3.com/diveintopython3/
http://www.greenteapress.com/thinkpython/

You're going to get a whole lot more out of NLTK if you learn some
programming and some Python.

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