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《Journal of Huazhong University of Science and Technology(Nature Science Edition)》 2010-02
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Feature selection using new document frequency and improved Tabu search

Zhu Haodong1,2 Zhong Yong1,2(1 Chengdu Institute of Computer Application,Chinese Academy of Sciences,Chengdu 610041,China;2 The Graduate School of the Chinese Academy of Sciences,Beijing 100039,China)  
Feature selection is the core research topic in text categorization.A document frequency method based on minimum word frequency was presented.Then RS and Tabu search were introduced,the problems in attribute reduction based on Tabu search were analyzed,and some corresponding solutions were provided.Subsequently,an attribute reduction method based on the improved Tabu search was proposed.Finally,a comprehensive feature selection method based on the above-mentioned two methods was provided.The comprehensive method firstly uses the document frequency method based on minimum word frequency to extract original features,and then employs the proposed attribute reduction method to optimize and eliminate redundancy.Experimental results show that the comprehensive method is betterthan IG,CHI and MI.
【Fund】: 四川省科技计划资助项目(2008GZ0003);; 四川省科技攻关项目(07GG006-019)
【CateGory Index】: TP391.3
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