Feature Selection Based on Mutual Information and Rough Set Theory
Haodong Zhu, Hongchan Li · Jisuanji gongcheng · 2011
(Abstract )Feature selection is research hotspot in text automatic categorization. Mutual Information(MI) is analyzed. And according to deficiency of MI, Rough Set(RS) is introduced and an attribute reduction algorithm based on relation union theory is proposed. A feature selection method based on MI and the proposed attribute reduction algorithm is presented, and it is suitable for massive text data sets. The method uses MI to select features, and employs the proposed attribute reduction algorithm to eliminate redundancy, so it can acquire the feature subsets which are more representative. Experimental results show that the method is promising.