Harmony Search applied for Support Vector Machines Training Optimization

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorPereira, Luis A. M.-
Autor(es): dc.creatorPapa, João Paulo-
Autor(es): dc.creatorSouza, Andre N. de-
Data de aceite: dc.date.accessioned2021-03-10T21:34:30Z-
Data de disponibilização: dc.date.available2021-03-10T21:34:30Z-
Data de envio: dc.date.issued2015-03-18-
Data de envio: dc.date.issued2015-03-18-
Data de envio: dc.date.issued2013-01-01-
Fonte completa do material: dc.identifierhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6625103-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/117647-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/117647-
Descrição: dc.descriptionSince the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.-
Formato: dc.format998-1002-
Idioma: dc.languageen-
Publicador: dc.publisherIeee-
Relação: dc.relation2013 Ieee Eurocon-
Direitos: dc.rightsopenAccess-
Palavras-chave: dc.subjectSupport Vector Machines-
Palavras-chave: dc.subjectHarmony Search-
Palavras-chave: dc.subjectFault Detections-
Título: dc.titleHarmony Search applied for Support Vector Machines Training Optimization-
Aparece nas coleções:Repositório Institucional - Unesp

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