def extract_features(tweet):
tot=extarctFeatures.extFeat("traindata1.csv")
featureList=tot[0]
tweet_words = set(tweet)
features = {}
for word in featureList:
features['contains(%s)' % word] = (word in tweet_words)
return features
def extBlk(filename):
whole=extarctFeatures.extFeat("traindata1.csv")
tweets=whole[1]
training_set=nltk.classify.util.apply_features(extract_features,tweets)
NBClassifier=nltk.NaiveBayesClassifier.train(training_set)
f1=open(filename)
f2=open('finalResults.txt','w')
for x in f1.readlines():
testTweet = x
processedTestTweet=preprocessTweets.processTweet(testTweet)
res=NBClassifier.classify(extract_features(extarctFeatures.getFeatures(processedTestTweet)))
f2.write(x+' '+res+'\n')
f1.close()
f2.close()
