def __init__(self, model, twitter_status): # Decode the twitter_status tm0 = time.strptime(twitter_status.created_at[:-6], '%a, %d %b %Y %H:%M:%S') self._time = time.mktime(tm0) self._user = twitter_status._user.screen_name self._message = filters.clean_text(twitter_status.text.encode('ascii', 'replace')) self._id = twitter_status._id # Score the decoded status if model: positive, self._score = model.classify(self._message) else: positive, self._score = False, 0.0 self._replyable = positive and filters.is_allowed_for_replying(self._message)
def get_test_score(training_tweets, test_tweets, test_indexes): model = Classifier(training_tweets) score = get_empty_score() fp = [] fn = [] for i, t in enumerate(test_tweets): a = t[0] p, log_odds = model.classify(t[1]) if do_filter: p = p and filters.is_allowed_for_replying(t[1]) score[(a, p)] += 1 if p != a: if p: fp.append((test_indexes[i], log_odds)) else: fn.append((test_indexes[i], log_odds)) return score, fp, fn
def get_test_score(training_tweets, test_tweets, test_indexes): model = Classifier(training_tweets) score = get_empty_score() fp = [] fn = [] for i,t in enumerate(test_tweets): a = t[0] p, log_odds = model.classify(t[1]) if do_filter: p = p and filters.is_allowed_for_replying(t[1]) score[(a,p)] += 1 if p != a: if p: fp.append((test_indexes[i], log_odds)) else: fn.append((test_indexes[i], log_odds)) return score, fp, fn
def __init__(self, model, twitter_status): # Decode the twitter_status tm0 = time.strptime(twitter_status.created_at[:-6], '%a, %d %b %Y %H:%M:%S') self._time = time.mktime(tm0) self._user = twitter_status._user.screen_name self._message = filters.clean_text( twitter_status.text.encode('ascii', 'replace')) self._id = twitter_status._id # Score the decoded status if model: positive, self._score = model.classify(self._message) else: positive, self._score = False, 0.0 self._replyable = positive and filters.is_allowed_for_replying( self._message)