Indiscernibility Relations by Interrelationships between Attributes in Rough Set Data Analysis

被引：0

作者：

Kudo, Yasuo ^{[1
]}

Murai, Tetsuya ^{[2
]}

机构：

[1] Muroran Inst Technol, Coll Informat & Syst, Mizumoto 27-1, Muroran, Hokkaido 0508585, Japan

[2] Hokkaido Univ, Grad Sch Informat Sci & Technol, Kita Ku, Sapporo, Hokkaido 0600814, Japan

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC 2012) | 2012年

关键词：

attribute reduction; decision logic; indiscernibility relation; interrelation; rough set;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Indiscernibilty of objects is a key concept of rough set theory, and from a viewpoint of reasoning about data in rough set data analysis, comparison of attribute values is a basis of indiscernibility of objects. However, the interrelations between attributes has not clearly considered as far as the authors know. In this paper, we discuss the importance of interrelationships between attributes in rough set data analysis, and introduce an approach to formulate and extract interrelationships between attributes from a given decision table.

引用

页码：220 / 225

页数：6

共 6 条

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[4] Rough sets theory for multicriteria decision analysis
Greco, S
Matarazzo, B
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[J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2001, 129 (01) : 1 - 47
[5] ROUGH SETS
PAWLAK, Z
[J]. INTERNATIONAL JOURNAL OF COMPUTER & INFORMATION SCIENCES, 1982, 11 (05): : 341 - 356
[6] Pawlak Z., 1991, Theoretical Aspects of Reasoning About Data, Rough sets, DOI [10.1007/978-94-011-3534-4, DOI 10.1007/978-94-011-3534-4]

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