A model for a complex polynomial SVM kernel

被引：0
作者：
Simian, Dana [1 ]
机构：
[1] Univ Lucian Blaga Sibiu, Fac Sci, Dept Comp Sci, Str Dr Ion Ratiu 5-7, Sibiu 550012, Romania
来源：
SMO 08: PROCEEDINGS OF THE 8TH WSEAS INTERNATIONAL CONFERENCE ON SIMULATION, MODELLING AND OPTIMIZATION | 2008年
关键词：
Multiple Kernel; SVM; Classification; Genetic Algorithm;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
SVM models are obtained by convex optimization and are able to learn and generalize in high dimensional input spaces. The kernel method is a very powerful idea. Using an appropriate kernel, the data are projected in a space with higher dimension in which they are separable by an hyperplane. Usually simple kernels are used but the real problems require more complex kernels. The aim of this paper is to introduce and analyze a multiple kernel based only on simple polynomials kernels.
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页码：164 / +
页数：3
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