class Classifier(object):
def __init__(self):
self.classifier = NaiveBayes()
def learn_from_tweets(self, user_ids, category):
"""
Train the classifier by tweets.
user_ids : A list of twitter ids which their tweets are included
in the category.
category : The category of the tweets.
"""
tweets = get_tweets(user_ids)
categories = [category] * len(tweets)
self.classifier.fit(tweets, categories)
print("Training...")
def predict_user_input(self):
"""Read user input until 'exit' is entered"""
sentence = input("input =>")
while(sentence != 'exit'):
category = self.classifier.predict_(sentence)
print("{}\n".format(category))
sentence = input("input =>")
def save(self, filename):
"""Save the model."""
self.classifier.dump_json(filename)
def load(self, filename):
"""Load the model from a file."""
self.classifier.load_json(filename)
class Classifier(object):
def __init__(self):
self.classifier = NaiveBayes()
def learn_from_tweets(self, user_ids, category):
"""
Train the classifier by tweets.
user_ids : A list of twitter ids which their tweets are included
in the category.
category : The category of the tweets.
"""
tweets = get_tweets(user_ids)
categories = [category] * len(tweets)
self.classifier.fit(tweets, categories)
print("Training...")
def predict_user_input(self):
"""Read user input until 'exit' is entered"""
sentence = input("input =>")
while (sentence != 'exit'):
category = self.classifier.predict_(sentence)
print("{}\n".format(category))
sentence = input("input =>")
def save(self, filename):
"""Save the model."""
self.classifier.dump_json(filename)
def load(self, filename):
"""Load the model from a file."""
self.classifier.load_json(filename)
