def drill():
from random import shuffle
scored_texts = utils.load_tsv_file(NPS_FILE)
#shuffle(scored_texts)
c = classifier.NPSClassifier()
bar = int(len(scored_texts) * 0.75)
shuffle(scored_texts)
train, test = scored_texts[:bar], scored_texts[bar:]
c.train(train)
tested = 0
correct = 0
for comment, score in test:
guessed_score = c.classify(comment)
print '%8s (%8s) %s' % (guessed_score, score, sorted(comment.keys()))
tested += 1
if guessed_score == score:
correct += 1
print '\n' * 5
print "Tested: %d" % tested
print "Correct: %d" % correct
print "Accuracy: %0.3f" % (float(correct) / float(tested))
def main():
z = utils.load_tsv_file(NPS_FILE)
build_classifier(z)
