Topological reduction approaches for relation decision systems

被引:3
|
作者
Xie, Yehai [1 ]
Gao, Xiuwei [1 ]
机构
[1] Beijing Language & Culture Univ, Sch Informat Sci, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
Attribute reduction; Rough set; Relation decision system; Topological reduction; Discernibility matrix; ATTRIBUTE REDUCTION; ROUGH; APPROXIMATION; DISCERNIBILITY; SETS;
D O I
10.1016/j.ijar.2023.03.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this study, we use topological methods to investigate attribute reduction problems for relation decision systems. We propose the notions of topological consistent and inconsistent relation decision systems. Then, we propose the concept of the consistent topological reduction of topological consistent relation decision systems. To enlarge the scope of application, we define the general topological reduction of relation decision systems, which is a further generalization of consistent topological reduction. Moreover, we develop corresponding reduction algorithms for these two types of reductions. To demonstrate that our algorithms cannot be unified by the general reduction algorithm, we discuss the relationship between the consistent topological reducts and the reducts identified by the general reduction algorithm. We conduct numerical experiments on 11 UCI datasets to verify our theoretical results. The experimental results demonstrate that the proposed reduction algorithms are effective and practicable.& COPY; 2023 Elsevier Inc. All rights reserved.
引用
收藏
页码:33 / 48
页数:16
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