Example #1
0
 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) 
Example #2
0
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
Example #3
0
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
Example #4
0
    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)