Journal of University of Chinese Academy of Sciences >
Model selection for SVM classification based on kernel prototype and adaptive genetic algorithm
Received date: 2010-11-26
Revised date: 2011-01-28
Online published: 2012-01-15
Model selection plays an important role in support of vector machine classification. We propose a concept of kernel prototype which means general kernel type. Based on this, a new algorithm for model selection for supporting vector machine classification is proposed. The powerful adaptive genetic algorithm is used to optimize the parameters in kernel prototype, and it can find the optimal kernel type as well as the kernel parameters. Experiments show effectiveness and stability of the algorithms.
CHEN Gang , WANG Hong-Qi , SUN Xian . Model selection for SVM classification based on kernel prototype and adaptive genetic algorithm[J]. Journal of University of Chinese Academy of Sciences, 2012 , 29(1) : 62 -69 . DOI: 10.7523/j.issn.2095-6134.2012.1.009
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