tfbns 0.0.3

A Python package for Term Frequency - Binomial Seperation feature scaling

 Tfbns is an open source python library for Binomial Seperation Feature Scaling. BNS is an improved feature representation over Term Frequency - Inverse Document Frequency (TFIDF) representation for SVM Text classification. The implementation of the library is based on the paper: "Forman, G. (2008, October). BNS feature scaling: an improved representation over tf-idf for svm text classification. In Proceedings of the 17th ACM conference on Information and knowledge management (pp. 263-270)".

Usage:

from tfbns.feature_extraction import tfbns

	df = pd.read_csv("data.csv")
	tfbns_vectorizer = Tfbns()
	x_train = df['text'].to_numpy()
	y_train = df['label'].to_numpy() 
	#Label should be binary containing 0 or 1
	x_train_tfbns = tfbns.fit_transform(x_train, y_train)
	x_test_tfbns = tfbns.transform(x_test)