Fuzzy rough set based incremental attribute reduction from dynamic data with sample arriving

2017 ◽  
Vol 312 ◽  
pp. 66-86 ◽  
Author(s):  
Yanyan Yang ◽  
Degang Chen ◽  
Hui Wang ◽  
Eric C.C. Tsang ◽  
Deli Zhang
Keyword(s):  
Rough Set ◽  
Attribute Reduction ◽  
Fuzzy Rough Set ◽  
Dynamic Data

scholarly journals About a Fuzzy Distance between Two Fuzzy Partitions and Application in Attribute Reduction Problem

2016 ◽  
Vol 16 (4) ◽  
pp. 13-28 ◽  
Author(s):  
Cao Chinh Nghia ◽  
Demetrovics Janos ◽  
Nguyen Long Giang ◽  
Vu Duc Thi
Keyword(s):  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Reduction ◽  
Data Sets ◽  
Theory Approach ◽  
Fuzzy Rough Set ◽  
Fuzzy Distance ◽  
Reduction Methods ◽  
Fuzzy Partitions ◽  
Decision Tables

Abstract According to traditional rough set theory approach, attribute reduction methods are performed on the decision tables with the discretized value domain, which are decision tables obtained by discretized data methods. In recent years, researches have proposed methods based on fuzzy rough set approach to solve the problem of attribute reduction in decision tables with numerical value domain. In this paper, we proposeafuzzy distance between two partitions and an attribute reduction method in numerical decision tables based on proposed fuzzy distance. Experiments on data sets show that the classification accuracy of proposed method is more efficient than the ones based fuzzy entropy.

Fuzzy rough set based attribute reduction for information systems with fuzzy decisions

2011 ◽  
Vol 24 (5) ◽  
pp. 689-696 ◽  
Author(s):  
Qiang He ◽  
Congxin Wu ◽  
Degang Chen ◽  
Suyun Zhao
Keyword(s):  
Information Systems ◽  
Rough Set ◽  
Attribute Reduction ◽  
Fuzzy Rough Set
Sign in / Sign up

Export Citation Format

Share Document