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Type: Artigo de evento
Title: Ga-based Selection Of Components For Heterogeneous Ensembles Of Support Vector Machines
Author: Coelho A.L.V.
Lima C.A.M.
Von Zuben F.J.
Abstract: Several support vector machine (SVM) instances with distinct kernel functions may be separately created and properly combined into the same learning machine structure. This is the idea underlying heterogeneous ensembles of SVMs (HE-SVMs), an approach conceived to alleviate the performance bottlenecks incurred with the kernel function choice problem inherent in SVM design. In this paper, we assess the effectiveness of applying an evolutionary based mechanism (GASe1) in the search of the optimal subset of SVM models for automatic HE-SVM construction. GASe1 has the advantage of merging both the selection and combination of component SVMs into the same optimization process, and has shown sound performance when compared with two other component selection methods in complicated classification problems. © 2003 IEEE.
Editor: IEEE Computer Society
Rights: fechado
Identifier DOI: 10.1109/CEC.2003.1299950
Date Issue: 2003
Appears in Collections:Unicamp - Artigos e Outros Documentos

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