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Combined multiple svm classifiers based on Choquet integral with respect to L- measure

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3 Author(s)
Wen-Chih Lin ; Dept. of Comput. Sci. & Inf. Eng., Asia Univ., Taichung, Taiwan ; Chih-Sheng Huang ; Wen-Chun Huang

Combining multiple classifiers is a natural way to explore useful information and improve the performances of individual classifiers. Support vector machine (SVM) has an excellent ability to solve the classification problems. In this study, we try to combine the multiple SVMs which is desirous to gain a more accurate classification than single SVM. When interactions exist in combining multiple SVMs, fuzzy integral with respect to L-measure would be a valid method to fuse these multiple SVMs. From this experiment results, the fusion method based on this fuzzy fusion obtains advancement in terms of the performance of classification.

Published in:

Machine Learning and Cybernetics, 2009 International Conference on  (Volume:6 )

Date of Conference:

12-15 July 2009