Fast assignment reduction in inconsistent incomplete decision systems

被引：0

作者：

Min Li ^{[1
,2
,3
]}

Shaobo Deng ^{[1
,4
,3
]}

Shengzhong Feng ^{[1
]}

Jianping Fan ^{[1
]}

机构：

[1] Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences

[2] Nanchang Institute of Technology

[3] Graduate School of Chinese Academy of Sciences

[4] Key Laboratory of Intelligent Information Processing,Institute of Computing Technology,Chinese Academy of Sciences

来源：

JournalofSystemsEngineeringandElectronics | 2014年 / 25卷 / 01期

基金：

中国国家自然科学基金;

关键词：

assignment reduction; upper approximation reduction; inconsistent incomplete decision system; rough set;

D O I：

暂无

中图分类号：

O225 [对策论（博弈论）];

学科分类号：

070105 ; 1201 ;

摘要：

This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly according to its definition. We propose the judgment theorem for the assignment reduct in the inconsistent incomplete decision system, which greatly simplifies judging this type reduct. On such basis, we derive a novel attribute significance measure and construct the fast assignment reduction algorithm(FARA), intended for computing the assignment reduct in inconsistent incomplete decision systems. Finally, we make a comparison between FARA and the discernibility matrixbased method by experiments on 13 University of California at Irvine(UCI) datasets, and the experimental results prove that FARA is efficient and feasible.

引用

页码：83 / 94

页数：12

共 18 条

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