PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Radius-Margin Bound on the Leave-One-Out Error of the LLW-M-SVM
Yann Guermeur and E. Monfrini
In: ASMDA 2009, 30 Jun - 2 Jul 2009, Vilnius, Lithuania.

Abstract

To set the values of the hyperparameters of a support vector machine (SVM), one can use cross-validation. Its leave-one-out variant produces an estimator of the generalization error which is almost unbiased. Its major drawback rests in its time requirement. To overcome this difficulty, several upper bounds on the leave-one-out error of the pattern recognition SVM have been derived. The most popular one is the radius-margin bound. In this article, we introduce a generalized radius-margin bound dedicated to the multi-class SVM of Lee, Lin and Wahba.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:6619
Deposited By:Yann Guermeur
Deposited On:08 March 2010