A User’s Guide to Support Vector Machines

  • Asa Ben-Hur
  • Jason Weston
Part of the Methods in Molecular Biology book series (MIMB, volume 609)


The Support Vector Machine (SVM) is a widely used classifier in bioinformatics. Obtaining the best results with SVMs requires an understanding of their workings and the various ways a user can influence their accuracy. We provide the user with a basic understanding of the theory behind SVMs and focus on their use in practice. We describe the effect of the SVM parameters on the resulting classifier, how to select good values for those parameters, data normalization, factors that affect training time, and software for training SVMs.

Key words

Kernel methods Support Vector Machines (SVM) 



The authors would like to thank William Noble for comments on the manuscript.


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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Asa Ben-Hur
    • 1
  • Jason Weston
    • 2
  1. 1.Department of Computer ScienceColorado State UniversityFort CollinsUSA
  2. 2.NEC Labs AmericaPrincetonUSA

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