Minimum cost attribute reduction algorithms for incomplete neighborhood decision-theoretic rough set

Yao Shenga,b
Li Chuyana,b
Wu Zhaoyua,b
a. College of Computer Science & Technology, b. Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Hefei 230601, China

Abstract

The current research on decision-theoretic rough sets mainly focuses on the complete discrete information system, and few studies on incomplete continuous data. Considering this problem, this paper proposed an incomplete neighborhood decision-theoretic rough set model. Firstly, it introduced incomplete neighborhood relation into incomplete continuous data, and then reconstructed the traditional decision-theoretic rough sets by the binary relation, proposed a model called incomplete neighborhood decision-theoretic rough sets. At the same time, based on the principle of decision cost, it proposed an attribute reduction algorithm to minimize the decision cost. Finally, experiments show that the proposed algorithm has better performance in attribute reduction.

Foundation Support

国家自然科学基金资助项目(61602004,61300057)
安徽省自然科学基金资助项目(1508085MF127)
安徽省高等学校自然科学研究重点资助项目(KJ2016A041)
安徽大学信息保障技术协同创新中心公开招标课题资助项目(ADXXBZ20145,ADXXBZ20146)
安徽大学博士科研启动基金资助项目(J10113190072)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.09.0587
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 1
Section: Algorithm Research & Explore
Pages: 65-68
Serial Number: 1001-3695(2021)01-013-0065-04

Publish History

[2021-01-05] Printed Article

Cite This Article

姚晟, 李初宴, 吴照玉. 不完备邻域决策粗糙集的最小化代价属性约简算法 [J]. 计算机应用研究, 2021, 38 (1): 65-68. (Yao Sheng, Li Chuyan, Wu Zhaoyu. Minimum cost attribute reduction algorithms for incomplete neighborhood decision-theoretic rough set [J]. Application Research of Computers, 2021, 38 (1): 65-68. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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