Gacv for support vector machines

@inproceedings{Wahba2000GacvFS,
  title={Gacv for support vector machines},
  author={Grace Wahba and Yuan Yao Lin and Hansong Zhang},
  year={2000}
}
We introduce the Generalized Approximate Cross Validation (GACV) for estimating tuning parameter(s) in SVMs. The GACV has as its target the choice of parameters which will minimize the Generalized Comparative Kullback-Leibler Distance (GCKL). The GCKL is seen to be an upper bound on the expected misclassifica-tion rate. Some modest simulation examples suggest how it might work in practice. The GACV is the sum of a term which is the observed (sample) GCKL plus a margin-like quantity. reproducing… CONTINUE READING

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