Multi-objective model selection for support vector machines

Christian Igel*

*Corresponding author af dette arbejde
44 Citationer (Scopus)

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.

OriginalsprogEngelsk
TitelEvolutionary Multi-Criterion Optimization : Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005. Proceedings
RedaktørerCarlos A. Coello Coello, Arturo Hernándex Aguirre, Eckart Zitzler
Antal sider13
ForlagSpringer
Publikationsdato2005
Sider534-546
ISBN (Trykt)978-3-540-24983-2
ISBN (Elektronisk)978-3-540-31880-4
DOI
StatusUdgivet - 2005
Udgivet eksterntJa
Begivenhed3rd International Conference on Evolutionary Multi-Criterion Optimization - Guanajuato, Mexico
Varighed: 9 mar. 200511 mar. 2005
Konferencens nummer: 3

Konference

Konference3rd International Conference on Evolutionary Multi-Criterion Optimization
Nummer3
Land/OmrådeMexico
ByGuanajuato
Periode09/03/200511/03/2005
NavnLecture notes in computer science
Vol/bind3410
ISSN0302-9743

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