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https://doi.org/10.1109/FUZZY.2008.4630431
Title: | EFSVM-FCM: Evolutionary fuzzy rule-based support vector machines classifier with FCM clustering | Authors: | Wee, C.T. Wan, T.W. |
Issue Date: | 2008 | Citation: | Wee, C.T.,Wan, T.W. (2008). EFSVM-FCM: Evolutionary fuzzy rule-based support vector machines classifier with FCM clustering. IEEE International Conference on Fuzzy Systems : 606-612. ScholarBank@NUS Repository. https://doi.org/10.1109/FUZZY.2008.4630431 | Abstract: | This paper presents a hybrid TSK fuzzy rule-based classifier. Fuzzy c-means clustering and Genetic algorithm and are used to optimize the number of rules and antecedent parameters. By using the relationship between a SVM and a TSK FLS, an efficient method for learning the consequent parts of the TSK fuzzy system is introduced. The resulting hybrid fuzzy classifier has a compact rule base and good generalization capabilities compared to existing algorithms in the literature. In this sense, the curse of dimensionality which is often associated with fuzzy rule-based classifier can be avoided. The performance of the proposed hybrid fuzzy classifier is verified through extensive tests and comparison with other methods. © 2008 IEEE. | Source Title: | IEEE International Conference on Fuzzy Systems | URI: | http://scholarbank.nus.edu.sg/handle/10635/70118 | ISBN: | 9781424418190 | ISSN: | 10987584 | DOI: | 10.1109/FUZZY.2008.4630431 |
Appears in Collections: | Staff Publications |
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