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.
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Rocha Neto, A.R., Barreto, G.A. (2011). A Novel Heuristic for Building Reduced-Set SVMs Using the Self-Organizing Map. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21501-8_13
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DOI: https://doi.org/10.1007/978-3-642-21501-8_13
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