DocumentCode
2754225
Title
Decision Rule Generation Based on Similarity Relation*
Author
An, Liping ; Tong, Lingyun
Author_Institution
Bus. Sch., Nankai Univ., Tianjin
Volume
2
fYear
0
fDate
0-0 0
Firstpage
5915
Lastpage
5918
Abstract
The indiscernibility relation is the mathematical basis for the classical rough set theory. It is natural to extend the indiscernibility relation originally used for the definition of the rough approximation when the data describing objects is imprecise or when small differences are meaningless in the context of the study. This situation can be modeled using a binary relation that represents a certain form of similarity. Based on the concepts of lower and upper approximations using the similarity relation, the nonsimilarity matrix and the nonsimilarity function are presented to induce the minimal decision rules. An example is illustrated to demonstrate the application of this new approach
Keywords
decision theory; function approximation; matrix algebra; rough set theory; binary relation; decision rule generation; indiscernibility relation; minimal decision rules; nonsimilarity function; nonsimilarity matrix; rough approximation; rough set theory; similarity relation; Fuzzy sets; Rough sets; Set theory; Technology management; Decision rules; Rough sets; Rule generation; Similarity relation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location
Dalian
Print_ISBN
1-4244-0332-4
Type
conf
DOI
10.1109/WCICA.2006.1714213
Filename
1714213
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