Ensemble Methods of Appropriate Capacity for Multi-Class Support Vector Machines
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.
|EPrint Type:||Conference or Workshop Item (Paper)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Subjects:||Theory & Algorithms|
|Deposited By:||Yann Guermeur|
|Deposited On:||08 March 2010|