FCA Attribute Reduction in Information Systems

被引：5
|
作者：
Jose Benitez-Caballero, M. [1 ]
Medina, Jesus [1 ]
Ramirez-Poussa, Eloisa [1 ]
机构：
[1] Univ Cadiz, Dept Math, Cadiz, Spain
来源：
INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: THEORY AND FOUNDATIONS, IPMU 2018, PT I | 2018年 / 853卷
关键词：
Formal concept analysis; Rough set; Attribute reduction; ROUGH SETS; ADJOINT;
D O I：
10.1007/978-3-319-91473-2_47
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
One of the main targets in formal concept analysis (FCA) and in rough set theory (RST) is the reduction of redundant information. Feature selection mechanisms have been studied separately in many works. In this paper, we analyse the result of applying the reduction mechanisms given in FCA to RST, and give interpretations of such reductions.
引用
收藏
页码：549 / 561
页数：13
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