Radius-margin Bound on the Leave-one-out Error of Multi-class SVMsReport as inadecuate




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1 MODBIO - Computational models in molecular biology INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications

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.

Keywords : M-SVMS MODEL SELECTION LEAVE-ONE-OUT ERROR SVMS





Author: Yannick Darcy - Yann Guermeur -

Source: https://hal.archives-ouvertes.fr/



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