收稿日期: 2010-11-26
修回日期: 2011-01-28
网络出版日期: 2012-01-15
基金资助
国家自然科学基金(41001285)资助
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
陈刚 , 王宏琦 , 孙显 . 基于核函数原型和自适应遗传算法的 SVM模型选择方法[J]. 中国科学院大学学报, 2012 , 29(1) : 62 -69 . DOI: 10.7523/j.issn.2095-6134.2012.1.009
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.
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