def run_for_set():
start_time = LoggingUtil.log_start_time()
data = DataUtil.prepare_data()
cls = classifier.Classifier()
cls.perform_with_cross_validation(data, load_from_pickle=False)
LoggingUtil.log_end_time(start_time)
def run_for_examples():
start_time = LoggingUtil.log_start_time()
data = DataUtil.prepare_data()
cls = MultinomialNB()
vect = CountVectorizer(ngram_range=(1, 2))
train_labels = data['label'].values
train_features = vect.fit_transform(data['email'].values)
cls.fit(train_features, train_labels)
examples = ['Congrats! Boss is proud of your promotion. Keep doing well. Regards.',
'Congrats! You are lucky one to be offered a promotion!',
'Congrats! You are promoted!',
'Congrats! You won one million!']
test_features = vect.transform(examples)
predictions = cls.predict(test_features)
print(predictions)
LoggingUtil.log_end_time(start_time)