Paper Info
Title
Indiscernibility relations by interrelationships between attributes in rough set data analysis
Abstract
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.
Year
DOI
Venue
2012
10.1109/GrC.2012.6468687
GrC
Keywords
Field
DocType
data analysis,rough set theory,decision theory
Decision table,Pattern recognition,Computer science,Rough set,Artificial intelligence,Decision theory,Dominance-based rough set approach
Conference
Citations 
PageRank 
References 
4
0.53
1
Authors
2
Name
Order
Citations
PageRank
Yasuo Kudo19526.41
Tetsuya Murai218642.10