Editing Support Vector Machines

@inproceedings{Ke2001EditingSV,
  title={Editing Support Vector Machines},
  author={Haixin Ke and Xuegong Zhang},
  year={2001}
}
A support vector machine constructs an optimal hyperplane from a small set of samples near the boundary. This makes it sensitive to these specific samples and tends to result in machines either too complex with poor generalization ability or too imprecise with high training error, depending on the kernel parameters. In this paper, we present an improved version of the method, called editing support vector machine or ESVM, which removes some samples near the boundary from the training set… CONTINUE READING
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References

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Pattern Recognition, 2nd ed., Beijing

  • Z. Bian, X. Zhang
  • 2000
1 Excerpt

Using class-center vectors to build support vector machines

  • Xuegong Zhang
  • Neural Networks for Signal Processing IX,
  • 1999
2 Excerpts

Support Vector Machines for Classification and Regression, ISIS

  • Steve Gunn
  • (RBF width σ =0.3,
  • 1998

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