PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Ensemble Methods of Appropriate Capacity for Multi-Class Support Vector Machines
Yann Guermeur
In: SMTDA 2010, 8 Jun - 11 Jun 2010, Chania, Greece.

Abstract

Roughly speaking, there is one single model of pattern recognition support vector machine (SVM), with variants of lower popularity. On the contrary, among the different multi-class SVMs (M-SVMs) published, none is clearly favoured. Although several comparative studies between M-SVMs and decomposition methods have been reported, no attention had been paid so far to the combination of those models. We investigate the combination of M-SVMs with low capacity linear ensemble methods that estimate the class posterior probabilities.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:6620
Deposited By:Yann Guermeur
Deposited On:08 March 2010