DocumentCode :
2329222
Title :
Decision rule extraction method based on rough set theory and fuzzy set theory
Author :
Wang, Mingi-Chun ; Wang, Zenc-Ou ; ZHang, Ming ; Yan, Peng
Author_Institution :
Dept. of Syst. Eng., Tianjin Univ., China
Volume :
4
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
2212
Abstract :
A quantitative decision table can be transformed into a qualitative decision one by using the fuzzy set theory. This paper develops the definition of membership function mentioned in the literature, and proposes transforming rules from the quantitative decision table to the qualitative decision table with the properties of membership function. The rules can change an n-dimension quantitative decision table into an n-dimension qualitative decision table instead of a 3n-dimension one. So it greatly decreases afterward computing complexity of rule extraction using rough set theory, while increases the quality of extracted rules.
Keywords :
data mining; decision tables; fuzzy set theory; rough set theory; decision rule extraction method; fuzzy set theory; membership function; qualitative decision table; quantitative decision table; rough set theory; Computer science education; Cybernetics; Fuzzy set theory; Hip; Machine learning; Medical diagnosis; Set theory; Tellurium; Decision Table; Fuzzy Set; Rough Set; Rule Extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527312
Filename :
1527312
Link To Document :
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