Abstract
In this article, model selection for support vector machines is viewed as a multi-objective optimization problem, where model complexity and training accuracy define two conflicting objectives. Different optimization criteria are evaluated: Split modified radius margin bounds, which allow for comparing existing model selection criteria, and the training error in conjunction with the number of support vectors for designing sparse solutions.
Originalsprog | Engelsk |
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Titel | Evolutionary Multi-Criterion Optimization : Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005. Proceedings |
Redaktører | Carlos A. Coello Coello, Arturo Hernándex Aguirre, Eckart Zitzler |
Antal sider | 13 |
Forlag | Springer |
Publikationsdato | 2005 |
Sider | 534-546 |
ISBN (Trykt) | 978-3-540-24983-2 |
ISBN (Elektronisk) | 978-3-540-31880-4 |
DOI | |
Status | Udgivet - 2005 |
Udgivet eksternt | Ja |
Begivenhed | 3rd International Conference on Evolutionary Multi-Criterion Optimization - Guanajuato, Mexico Varighed: 9 mar. 2005 → 11 mar. 2005 Konferencens nummer: 3 |
Konference
Konference | 3rd International Conference on Evolutionary Multi-Criterion Optimization |
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Nummer | 3 |
Land/Område | Mexico |
By | Guanajuato |
Periode | 09/03/2005 → 11/03/2005 |
Navn | Lecture notes in computer science |
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Vol/bind | 3410 |
ISSN | 0302-9743 |