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.


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