Approach for absolute attribute reductions in rough sets

被引：0
|
作者：
Pei, Xiao-Bing [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Coll Software, Wuhan 430074, Peoples R China
来源：
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年
关键词：
rough set; absolute attribute reduction;
D O I：
10.1109/ICMLC.2008.4620437
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Attribute reductions is one of the basic contents in rough sets and one of the most problem in knowledge acquisition. At present, the methods used are often Pawlak's data analysis and Skowron's discernible matrix methods. In this paper an approach for the set of all absolute attribute reductions is proposed based on the discernible attribute set. Finally, we also show the experimental results by examples.
引用
收藏
页码：391 / 394
页数：4
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