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Erschienen in:
2008 | OriginalPaper | Buchkapitel
A Class of Novel Kernel Functions
verfasst von : Xinfei Liao, Limin Tao
Erschienen in: Intelligent Data Engineering and Automated Learning – IDEAL 2008
Verlag: Springer Berlin Heidelberg
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This paper proposes a kind of novel kernel functions obtained from the reproducing kernels of Hilbert spaces associated with special inner product. SVM with the proposed kernel functions only need less support vectors to construct two-class hyperplane than the SVM with Gaussian kernel functions, so the proposed kernel functions have the better generalization. Finally, SVM with reproducing and Gaussian kernels are respectively applied to two benchmark examples: the well-known Wisconsin breast cancer data and artificial dataset.