Midpoint-validation algorithm for support vector machine classification

Authors:
Hiroki Tamura;Shingo Yamashita;Koichi Tanno
Affiliations:
Faculty of Engineering, University of Miyazaki, Miyazaki, Japan 889-2192;Faculty of Engineering, University of Miyazaki, Miyazaki, Japan 889-2192;Faculty of Engineering, University of Miyazaki, Miyazaki, Japan 889-2192
Venue:
Artificial Life and Robotics
Year:
2010

Citing 7
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Abstract

In this article, we propose a midpoint-validation algorithm for a support vector machine which improves the generalization of the support vector machine so that the midpoint-validation error is minimized. We compared its performance with other techniques for support vector machines, and also tested our proposed method on fifth benchmark problems. The results obtained from the simulation shows the effectiveness of the proposed method.