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.
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This work was presented in part at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010
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Tamura, H., Yamashita, S. & Tanno, K. Midpoint-validation algorithm for support vector machine classification. Artif Life Robotics 15, 138–141 (2010). https://doi.org/10.1007/s10015-010-0779-6
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DOI: https://doi.org/10.1007/s10015-010-0779-6