A global search algorithm for attributes reduction

	A global search algorithm for attributes reduction
	Tan, S
	2004
发表期刊	AI 2004: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS
ISSN	0302-9743
卷号	3339 页码:1004-1010
摘要	Attributes reduction is a crucial problem in rough set application to data mining. In this paper, we introduce the Universal RED problem model, or UniRED, which transforms the discrete attributes reduction problems on Boolean space into continuous global optimization problems on real space. Based on this transformation, we develop a coordinate descent algorithm RED2.1 for attributes reduction problems. In order to examine the efficiency of our algorithms, we conduct the comparison between our algorithm RED2.1 and other reduction algorithms on some problems from UCI repository. The experimental results indicate the efficiency of our algorithm.
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000226133600093
出版者	SPRINGER-VERLAG BERLIN
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/13830
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Tan, S
作者单位	1.Chinese Acad Sci, Software Dept, Inst Comp Technol, Beijing 100864, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing 100864, Peoples R China
推荐引用方式 GB/T 7714	Tan, S. A global search algorithm for attributes reduction[J]. AI 2004: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS,2004,3339:1004-1010.
APA	Tan, S.(2004).A global search algorithm for attributes reduction.AI 2004: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS,3339,1004-1010.
MLA	Tan, S."A global search algorithm for attributes reduction".AI 2004: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS 3339(2004):1004-1010.