An Improved Attribute Reduction Algorithm Based on Importance of Attribute Value

被引：1
|
作者：
Li, Ju [1 ]
Fan, Xiaowen [1 ]
Wang, Xing [2 ]
机构：
[1] Chang Shu Inst Technol, Sch Engn & Comp Sci, Changshu 215500, Jiangsu, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Jiangsu, Peoples R China
来源：
2010 SYMPOSIUM ON SECURITY DETECTION AND INFORMATION PROCESSING | 2010年 / 7卷
关键词：
rough set; attribute reduction; restrictive positive region; heuristic algorithm;
D O I：
10.1016/j.proeng.2010.11.057
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The theory of rough set is a new mathematical tool to deal with the uncertain problems, and the attribute reduction is one of key problems in the theory. To obtain a better method of attributes reduction in decision-making system, a concept of restrictive positive region was proposed. The method using positive region and restrictive positive region which have been obtained, shrinks the scope of data processing, so that reduces the time demand. By an instance, the paper presents the application of this method, and confirms that the computation is reduced and the result could be simpler, using this algorithm compared with the traditional algorithm. Thus, it is proven that this method is a fast and efficient algorithm of attribute reduction. (c) 2009 Published by Elsevier Ltd.
引用
收藏
页码：356 / 359
页数：4
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