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|Title:||EFSVM-FCM: Evolutionary fuzzy rule-based support vector machines classifier with FCM clustering|
|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|
|Appears in Collections:||Staff Publications|
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