Feature extraction is a key point of text categorization. The accuracy of extraction will directly affect the accuracy of text classification. This paper introduces and compares 4 commonly used methods of text feature extraction: IG (Information gain), MI (Mutual information), CHI (x~2 statistics), DF (Document frequency), and proposes an improved method based on the method of CHI. Experiment result shows that the proposed method can improve the accuracy of text categorization.
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