Detecting Illegal Online Gambling (IOG) Services in the Mobile Environment

Algorithm 1

Deciding parameter of vectorizers.

	from sklearn.feature_extraction.text import TfidfVectorizer
	from sklearn.feature_extraction.text import CountVectorizer
	from sklearn.feature_extraction.text import HashingVectorizer
	class classifier:
	…
	def vectorize(self, opt3):
	…
	self.vectorizers = [TfidfVectorizer(tokenizer = self.tokenize,
	stop_words = self.stop_words, ngram_range = (1,4), min_df = 3, max_df = 0.9), CountVectorizer(tokenizer = self.tokenize, stop_words = self.stop_words, ngram_range = (1,2), min_df = 3, max_df = 0.9), HashingVectorizer(tokenizer = self.tokenize, stop_words = self.stop_words, ngram_range = (1,2))]