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
Link To Document :
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