#print ''
tags = getTags(scoresSort, test, mfs)
return tags
# ----------------------------------------------------------------- #
if __name__ == '__main__':
# file names
trainingFileA = 'trainA.txt'
trainingFileB = 'trainB.txt'
# parse training and testing data
trainA, testA = parseA(trainingFileA, 5)
trainB, testB = parseB(trainingFileB, 5)
# decision list
print '\nDECISION LIST Part 5'
tagsA = decisionList(trainA, testA)
tagsB = decisionList(trainB, testB)
checkTagsA(tagsA, testA)
checkTagsB(tagsB, testB)
# parse training and testing data
trainA, testA = parseA(trainingFileA, 4)
trainB, testB = parseB(trainingFileB, 4)
# decision list
print '\nDECISION LIST Part 4'
tagsA = decisionList(trainA, testA)
# print ''
tags = getTags(scoresSort, test, mfs)
return tags
# ----------------------------------------------------------------- #
if __name__ == "__main__":
# file names
trainingFileA = "trainA.txt"
trainingFileB = "trainB.txt"
# parse training and testing data
trainA, testA = parseA(trainingFileA, 5)
trainB, testB = parseB(trainingFileB, 5)
# decision list
print "\nDECISION LIST Part 5"
tagsA = decisionList(trainA, testA)
tagsB = decisionList(trainB, testB)
checkTagsA(tagsA, testA)
checkTagsB(tagsB, testB)
# parse training and testing data
trainA, testA = parseA(trainingFileA, 4)
trainB, testB = parseB(trainingFileB, 4)
# decision list
print "\nDECISION LIST Part 4"
tagsA = decisionList(trainA, testA)
# determine the number of weighted words in the tweet
for position in lexicon[word].keys():
if lexicon[word][position]['polar'] == 'positive':
pos += 1
elif lexicon[word][position]['polar'] == 'negative':
neg += 1
# tag the tweet
if pos > neg:
tagsB[ID][subject] = 'positive'
elif pos < neg:
tagsB[ID][subject] = 'negative'
else:
tagsB[ID][subject] = 'objective'
return tagsA, tagsB
# ----------------------------------------------------------------- #
if __name__ == '__main__':
trainingFileA = 'trainA.txt'
trainingFileB = 'trainB.txt'
lexiconFile = 'sentimentLexicon.txt'
trainA, testA = parseA(trainingFileA)
trainB, testB = parseB(trainingFileB)
lexicon = getSentimentWords(lexiconFile)
tagsA, tagsB = lexiconTag(trainA, trainB, lexicon)
checkTagsA(tagsA,trainA)
checkTagsB(tagsB,trainB)
# ----------------------------------------------------------------- #
