期刊
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
卷 8, 期 3, 页码 473-489出版社
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S021962200900348X
关键词
Data mining; fuzzy sets; simplified fuzzy rules; genetic algorithm; discriminant function
类别
资金
- National Science Council of Taiwan [NSC 97-2410-H-033-015-MY2]
A fuzzy if-then rule whose consequent part is a real number is referred to as a simplified fuzzy rule. Simplified fuzzy if-then rules have been widely used in function approximation problems due to no complicated defuzzification is required. The proposed simplified fuzzy rule-based classification system, whose number of output is equal to the number of different classes, approximates an unknown mapping from input to desired output for each discriminant function. Not only a fuzzy data mining method is proposed to find simplified fuzzy if-then rules from training data, but also the genetic algorithm is employed to determine some user-specified parameters. To evaluate the classification performance of the proposed method, computer simulations are performed on some well-known datasets, showing that the generalization ability of the proposed method is comparable to the other fuzzy or nonfuzzy methods.
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