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MP-Polynomial Kernel for Training Support Vector Machines

  • Iván Mejía-Guevara
  • Ángel Kuri-Morales
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4756)

Abstract

In this article we present a new polynomial function that can be used as a kernel for Support Vector Machines (SVMs) in binary classification and regression problems. We prove that this function fulfills the mathematical properties of a kernel. We consider here a set of SVMs based on this kernel with which we perform a set of experiments. Their efficiency is measured against some of the most popular kernel functions reported in the past.

Keywords

MP-Polynomial Kernel Kernel Methods Support Vector Machine 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Iván Mejía-Guevara
    • 1
  • Ángel Kuri-Morales
    • 2
  1. 1.Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), Universidad Nacional Autónoma de México (UNAM), Circuito Escolar S/N, CU, 04510 D. F.México
  2. 2.Departamento de Computación, Instituto Tecnológico Autónomo de México, Río Hondo No. 1, 01000 D. F.México

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