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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.

Keywords

SVM Reproducing Kernel 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xinfei Liao
    • 1
  • Limin Tao
    • 2
  1. 1.Department of ComputerWenzhou Vocational and Technical CollegeWenzhouChina
  2. 2.School of Information Science and EngineeringHangzhou Normal UniversityHangzhouChina

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