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A new ensemble learning with support vector machines

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2 Author(s)
Rameswar Debnath ; Department of Informatics, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, Japan ; Haruhisa Takahashi

Cascade of classifiers can, in general, improve the performance of any given classifier. In this paper, we present a new cascade classifier constructed with the support vector machine (SVM) classifiers where a set of SVMs is learned repeatedly with the bounded support vectors of the previous SVM. A binary decision tree is formed using the learned classifiers to take the decision of a new example. Experimental results show that the proposed method can improve the generalization performance over a single SVM.

Published in:

Computer and Information Application (ICCIA), 2010 International Conference on

Date of Conference:

3-5 Dec. 2010