A fast approach to attribute reduction in incomplete decision systems with tolerance relation-based rough sets

被引:151
作者
Meng, Zuqiang [1 ,2 ]
Shi, Zhongzhi [1 ]
机构
[1] Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
[2] Guangxi Univ, Coll Comp Elect & Informat, Nanning 530004, Peoples R China
基金
美国国家科学基金会;
关键词
Attribute reduction; Tolerance relation; Positive region; Incomplete decision system; Rough set theory; CONSISTENT; EXTENSIONS; SELECTION; RULES;
D O I
10.1016/j.ins.2009.04.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Efficient attribute reduction in large, incomplete decision systems is a challenging problem: existing approaches have time complexities no less than O(vertical bar C vertical bar(2)vertical bar U vertical bar(2)). This paper derives some important properties of incomplete information systems, then constructs a positive region-based algorithm to solve the attribute reduction problem with a time complexity no more than O(vertical bar C vertical bar(2)vertical bar U vertical bar log vertical bar U vertical bar). Furthermore, our approach does not change the size of the original incomplete system. Numerical experiments show that the proposed approach is indeed efficient, and therefore of practical value to many real-world problems. The proposed algorithm can be applied to both consistent and inconsistent incomplete decision systems. (c) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:2774 / 2793
页数:20
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