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Proceedings Paper

Support vector machines: heuristic of alternatives
Author(s): Marcin Orchel
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Paper Abstract

In this paper it will be presented Sequential Minimal Optimization (SMO) default heuristic optimization. SMO is an algorithm for solving Support Vector Machines (SVM) problem. SMO default heuristic chooses to the active set the worst two parameters based on the Karush-Kuhn-Tucker (KKT) conditions. The proposed heuristic of alternatives chooses parameters to the active set on the basis of not only KKT conditions, but also objective function value growth. Tests show that heuristic of alternatives is generally better than SMO default heuristic.

Paper Details

Date Published: 28 December 2007
PDF: 10 pages
Proc. SPIE 6937, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007, 69373D (28 December 2007); doi: 10.1117/12.784837
Show Author Affiliations
Marcin Orchel, AGH Univ. of Science and Technology (Poland)


Published in SPIE Proceedings Vol. 6937:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007

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