def classify_and_write_results(posts):
formatter = Format()
classifier = PostClassifier()
output_file = raw_input("Output file (empty defaults to stdout): ")
try:
f = open(output_file, 'w')
except IOError:
print 'Invalid filename entered. Printing dumped content ... '
f = None
for entry in posts:
entry.sentences = formatter.split_sentences(entry.body)
entry.sentences = zip(
entry.sentences, classifier.classify_sentiment(entry.sentences))
entry.label = classifier.classify_topic_unsupervised(entry.body)
output = '---POST---' + '\nauthor id: ' + str(entry.user_int_id) + \
'\nclass: ' + entry.label + '\nsentences and sentiments:\n' + \
'\n'.join(' : '.join(pair) for pair in entry.sentences)
if (f is not None):
f.write(output)
else:
print output
from classify import PostClassifier
train_path = raw_input("Path to training data: ")
lower_threshold = int(raw_input("Lower threshold: "))
negative_bucket = raw_input("Use negative bucket feature? (True/False): ") == "True"
classifier = PostClassifier()
classifier.sentiment_train(train_path, lower_threshold, negative_bucket)
while True:
sentence = raw_input("Sentence to classify: ")
print "Guess: " + classifier.classify_sentiment(sentence)