A new multi-class SVM based on a uniform convergence result
Identifieur interne : 00A291 ( Main/Exploration ); précédent : 00A290; suivant : 00A292A new multi-class SVM based on a uniform convergence result
Auteurs : Yann Guermeur [France] ; André Elisseeff ; Hélène Paugam-MoisySource :
English descriptors
Abstract
We introduce a new support vector machine devoted to the approximation of multi-class discriminant functions. Its training procedure consists in minimizing a new expression of the guaranteed risk. This bound is significantly tighter than the former ones, which should make the implementation of the structural risk minimization inductive principle in the context of multi-class discrimination better grounded.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
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Le document en format XML
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<front><div type="abstract" xml:lang="en">We introduce a new support vector machine devoted to the approximation of multi-class discriminant functions. Its training procedure consists in minimizing a new expression of the guaranteed risk. This bound is significantly tighter than the former ones, which should make the implementation of the structural risk minimization inductive principle in the context of multi-class discrimination better grounded.</div>
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