基于区分类别能力的高性能特征选择方法.pdfVIP

ISSN 1000-9825, CODEN RUXUEW E-mail: jos@ Journal of Software , Vol.19, No.1, January 2008, pp.82−89 DOI: 10.3724/SP.J.1001.2008.00082 Tel/Fax: +86-10 © 2008 by Journal of Software . All rights reserved. ∗ 基于区分类别能力的高性能特征选择方法 1,2+ 1 1 1,2 徐 燕 , 李锦涛 , 王 斌 , 孙春明 1( 中国科学院 计算技术研究所,北京 100080) 2(华北电力大学,北京 102206) A Category Resolve Power-Based Feature Selection Method 1,2+ 1 1 1,2 XU Yan , LI Jin-Tao , WANG Bin , SUN Chun-Ming 1(Institute of Computing Technology, The Chinese Academy of Sciences, Beijing 100080, China) 2(North China Electric Power University, Beijing 102206, China) + Corresponding author: Phn: +86-10 Fax: +86-10 E-mail: xuyan@ Xu Y, Li JT, Wang B, Sun CM. A category resolve power-based feature selection method. Journal of Software, 2008,19(1):82−89. /1000-9825/19/82.htm Abstract : One of the most important issues in Text Categorization (TC) is Feature Selection (FS). Many FS methods have been put forward and widely used in TC field, such as Information Gain (IG), Document Frequency (DF) thresholding, Mutual Information (MI) and so on. Empirical studies show that IG is one of the most effective methods, DF performs similarly, in contrast, and MI had relatively poor performance. One basic research question is why these FS methods cause different performance. Many existing work answers this question based on empirical studies. This paper presents a formal study of FS based on category resolve power. First, two desirable constraints that any reasonable FS function should satisfy