def classify_traffic(text,classifier):
pro_text = preprocessor().preprocess(text,[])
ft_pro_text = dict([(word, True) for word in pro_text])
label = classifier.classify(ft_pro_text)
isTraffic = False
probability = 0
#>>>>>>>>>>>>>>>>>>>>>FIND THE PROBABILITY<<<<<<<<<<<<<<<<<
if label == 'traffic':
isTraffic = True
probability_dict = classifier.prob_classify(ft_pro_text)
probability = probability_dict.prob('traffic')
print text, probability, isTraffic
return isTraffic, probability
def classify_traffic(text, classifier):
pro_text = preprocessor().preprocess(text, [])
ft_pro_text = dict([(word, True) for word in pro_text])
label = classifier.classify(ft_pro_text)
isTraffic = False
probability = 0
#>>>>>>>>>>>>>>>>>>>>>FIND THE PROBABILITY<<<<<<<<<<<<<<<<<
if label == 'traffic':
isTraffic = True
probability_dict = classifier.prob_classify(ft_pro_text)
probability = probability_dict.prob('traffic')
print text, probability, isTraffic
return isTraffic, probability
def classify_traffic(text, classifier):
pro_text = preprocessor().preprocess(text, [])
ft_pro_text = dict([(word, True) for word in pro_text])
label = classifier.classify(ft_pro_text)
isTraffic = False
probability = 0
# Find the probability
if label == 'traffic':
isTraffic = True
probability_dict = classifier.prob_classify(ft_pro_text)
probability = probability_dict.prob('traffic')
return isTraffic, probability
def classify_traffic(text, classifier):
pro_text = preprocessor().preprocess(text, [])
ft_pro_text = dict([(word, True) for word in pro_text])
label = classifier.classify(ft_pro_text)
isTraffic = False
probability = 0
# Find the probability
if label == "traffic":
isTraffic = True
probability_dict = classifier.prob_classify(ft_pro_text)
probability = probability_dict.prob("traffic")
return isTraffic, probability
