http://scholars.ntou.edu.tw/handle/123456789/6025
標題: | Tuning of the hyperparameters for L2-loss SVMs with the RBF kernel by the maximum-margin principle and the jackknife technique |
作者: | Chin-Chun Chang Shen-Huan Chou |
關鍵字: | RBF kernels;L2-loss support vector machines;The jackknife method;Maximum-margin principles |
公開日期: | 十二月-2015 |
卷: | 48 |
期: | 12 |
起(迄)頁: | 3983-3992 |
來源出版物: | Pattern Recognition |
摘要: | The hyperparameters for support vector machines (SVMs) with L2 soft margins and the radial basis function (RBF) kernel include the parameters for the RBF kernel and the L2-soft-margin parameter C. In this paper, the parameters for the RBF kernel are determined through maximization of a margin-based criterion. This criterion is approximately optimized through solving two easier subproblems: one is ... |
URI: | http://scholars.ntou.edu.tw/handle/123456789/6025 |
ISSN: | 0031-3203 |
DOI: | 10.1016/j.patcog.2015.06.017 |
顯示於: | 資訊工程學系 |
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