A Formal Concept Analysis Based Approach to Minimal Value Reduction

被引：0
|
作者：
Li, Mei-Zheng [1 ,2 ]
Wang, Guoyin [1 ,2 ,3 ]
Wang, Jin [2 ]
机构：
[1] Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Peoples R China
[2] Chongqing Univ Posts & Telecommun, Chongqing Key Lab Computat Intelligence, Chongqing 400065, Peoples R China
[3] Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Inst Elect & Informat Technol, Chongqing 401122, Peoples R China
来源：
ROUGH SETS AND KNOWLEDGE TECHNOLOGY: 8TH INTERNATIONAL CONFERENCE | 2013年 / 8171卷
关键词：
value reduction; rule acquisition; rough set; formal concept analysis; positive hypotheses; CONCEPT LATTICES; 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：
Reduction is a core issue in Rough Set Theory. Current reductions falls into 3 categories: tuple reduction, attribute reduction and value reduction. From the reduced tables, decision rules can be derived. For the purpose of storage and better understanding, minimization of the rule set is desired, and it is NP-hard. To tackle this problem, a heuristic approach to approximate minimal value reduct set is proposed based on Formal Concept Analysis in this paper. Experiments show that our approach is valid with a higher accuracy.
引用
收藏
页码：109 / 120
页数：12
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