A systematic study on attribute reduction with rough sets based on general binary relations

被引:154
作者
Wang, Changzhong [1 ]
Wu, Congxin [1 ]
Chen, Degang [2 ]
机构
[1] Harbin Inst Technol, Dept Math, Harbin 150001, Heilongjiang, Peoples R China
[2] N China Elect Power Univ, Dept Math & Phys, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
attribute reduction; discernibility matrix; rough sets based on general binary relations; relation information systems; relation decision systems;
D O I
10.1016/j.ins.2008.01.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
Attribute reduction is considered as an important preprocessing step for pattern recognition, machine learning, and data mining. This paper provides a systematic study on attribute reduction with rough sets based on general binary relations. We define a relation information system, a consistent relation decision system, and a relation decision system and their attribute reductions. Furthermore, we present a judgment theorem and a discernibility matrix associated with attribute reduction in each type of system; based on the discernibility matrix, we can compute all the reducts. Finally, the experimental results with UCI data sets show that the proposed reduction methods are an effective technique to deal with complex data sets. (c) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码:2237 / 2261
页数:25
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