A Class of Novel Kernel Functions

Authors:
Xinfei Liao;Limin Tao
Affiliations:
Department of Computer, Wenzhou Vocational and Technical College, Wenzhou, China 325035;School of Information Science and Engineering, Hangzhou Normal University, Hangzhou, China 310036
Venue:
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Year:
2008

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Abstract

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.