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Kernels for the Relevance Vector Machine - An Empirical Study

  • David Ben-Shimon
  • Armin Shmilovici
Part of the Studies in Computational Intelligence book series (SCI, volume 23)

Abstract

The Relevance Vector Machine (RVM) is a generalized linear model that can use kernel functions as basis functions. Experiments with the Matérn kernel indicate that the kernel choice has a significant impact on the sparsity of the solution. Furthermore, not every kernel is suitable for the RVM. Our experiments indicate that the Matérn kernel of order 3 is a good initial choice for many types of data.

Keywords

Machine Learning Relevance Vector Machine Kernel Regression Matérn Kernel 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • David Ben-Shimon
    • 1
  • Armin Shmilovici
    • 1
  1. 1.Dept. of Information Systems EngineeringBen-Gurion UniversityBeer-ShevaIsrael

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