A novel heuristic for building reduced-set SVMs using the self-organizing map

Authors:
Ajalmar R. Rocha Neto;Guilherme A. Barreto
Affiliations:
Federal Institute of Ceará, Campus of Maracanaú, Ceará, Brazil;Department of Teleinformatics Engineering, Federal University of Ceará, Center of Technology, Ceará, Brazil
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Year:
2011

Citing 8
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Abstract

We introduce a novel heuristic based on the Kohonen's SOM, called Opposite Maps, for building reduced-set SVM classifiers. When applied to the standard SVM (trained with the SMO algorithm) and to the LS-SVM method, the corresponding reduced-set classifiers achieve equivalent (or superior) performances than standard full-set SVMs.