A Study on Feature Selection in Chinese Text Categorization
LV Zhi-long · Computer Knowledge and Technology · 2007
This paper is a study of feature selection methods in text categorization. Seven methods ere evaluated, including document frequency (DF), information gain (IG), mutual information (MI), x2-test(CH I), Expected Cross Entropy(CE), Weight of Evidence for Text and Odds Ratio. DF relies on the high frequency word and MI, IG and CHI rely on the low frequency word. So feature selection method of a combined type is used and suppress effectively the lack of the high or low frequency word. Meanwhile we introduce a new feature selection method DFR. A furthermore experiment proved that the combined feature selection method is effective.