Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
第46回ISCIE「確率システム理論と応用」国際シンポジウム(2014年11月, 京都)
Randomized and Dimension Reduced Kernel Generation for Support Vector Machine
Akinori HidakaTakio Kurita
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ジャーナル フリー

2015 年 2015 巻 p. 191-196

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Generally, kernel support vector machines have several hyper-parameters which have to be determined by appropriate estimation methods. Usually, such hyper-parameters are fixed to same values for all learning samples. In this paper, we propose a novel kernel function based on usual radial basis function. We choose seeds of kernel function from learning samples at random, and we set randomized hyper-parameters for each kernel seed individually.
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© ISCIE Symposium on Stochastic Systems Theory and Its Applications
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