
Proceedings Paper
Support vector machines: heuristic of alternativesFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
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
Published in SPIE Proceedings Vol. 6937:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007
Ryszard S. Romaniuk, Editor(s)
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
Ryszard S. Romaniuk, Editor(s)
© SPIE. Terms of Use
