Radius-margin Bound on the Leave-one-out Error of Multi-class SVMs
Identifieur interne : 004874 ( Hal/Checkpoint ); précédent : 004873; suivant : 004875Radius-margin Bound on the Leave-one-out Error of Multi-class SVMs
Auteurs : Yannick Darcy [France] ; Yann Guermeur [France]Source :
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Abstract
Using a support vector machine requires to set two types of hyperparameters: the soft margin parameter C and the parameters of the kernel. To perform this model selection task, one can use various procedures based on cross-validation. Obviously, the major drawback of such procedures rests in their time requirements. To overcome this difficulty, several upper bounds on the leave-one-out error of pattern recognition support vector machines have been derived. In this report, we demonstrate a direct extension of one of these bounds, called the radius-margin bound, to the case of the standard multi-class SVM.
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Hal:inria-00070241Le document en format XML
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<front><div type="abstract" xml:lang="en">Using a support vector machine requires to set two types of hyperparameters: the soft margin parameter C and the parameters of the kernel. To perform this model selection task, one can use various procedures based on cross-validation. Obviously, the major drawback of such procedures rests in their time requirements. To overcome this difficulty, several upper bounds on the leave-one-out error of pattern recognition support vector machines have been derived. In this report, we demonstrate a direct extension of one of these bounds, called the radius-margin bound, to the case of the standard multi-class SVM.</div>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">Radius-margin Bound on the Leave-one-out Error of Multi-class SVMs</title>
<author role="aut"><persName><forename type="first">Yannick</forename>
<surname>Darcy</surname>
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<idno type="halAuthorId">97917</idno>
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<author role="aut"><persName><forename type="first">Yann</forename>
<surname>Guermeur</surname>
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<email>Yann.Guermeur@loria.fr</email>
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<monogr><idno type="reportNumber">RR-5780</idno>
<imprint><biblScope unit="pp">27</biblScope>
<date type="datePub">2005</date>
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<textClass><keywords scheme="author"><term xml:lang="en">M-SVMS</term>
<term xml:lang="en">MODEL SELECTION</term>
<term xml:lang="en">LEAVE-ONE-OUT ERROR</term>
<term xml:lang="en">SVMS</term>
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<abstract xml:lang="en">Using a support vector machine requires to set two types of hyperparameters: the soft margin parameter C and the parameters of the kernel. To perform this model selection task, one can use various procedures based on cross-validation. Obviously, the major drawback of such procedures rests in their time requirements. To overcome this difficulty, several upper bounds on the leave-one-out error of pattern recognition support vector machines have been derived. In this report, we demonstrate a direct extension of one of these bounds, called the radius-margin bound, to the case of the standard multi-class SVM.</abstract>
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