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(Neural Computation. 2007;19:1633-1655.)
© 2007 The MIT Press

Letter

Efficient Computation and Model Selection for the Support Vector Regression

Lacey Gunter

lgunter{at}umich.edu Department of Statistics, University of Michigan, Ann Arbor, MI 48109, U.S.A.

Ji Zhu

jizhu{at}umich.edu Department of Statistics, University of Michigan, Ann Arbor, MI 48109, U.S.A.

In this letter, we derive an algorithm that computes the entire solution path of the support vector regression (SVR). We also propose an unbiased estimate for the degrees of freedom of the SVR model, which allows convenient selection of the regularization parameter.






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Copyright © 2007 by The MIT Press.