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Erschienen in: Neural Computing and Applications 2/2014

01.08.2014 | Original Article

Support vector set selection using pulse-coupled neural networks

verfasst von: Yunxia Li, Zhang Yi, Jian Cheng Lv

Erschienen in: Neural Computing and Applications | Ausgabe 2/2014

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Abstract

A candidate set of support vectors is selected by using pulse-coupled neural networks to reduce computational cost in learning phase for support vector machines (SVMs). The size of the candidate set of support vectors selected this way is smaller than that of the original training samples so that the computation complexity in learning process for support vectors machines based on this candidate set is reduced and the learning process is accelerated. On the other hand, the candidate set of support vectors includes almost all support vectors, and the performance of the SVM based on this candidate set matches the performance when the full training samples are used.

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Metadaten
Titel
Support vector set selection using pulse-coupled neural networks
verfasst von
Yunxia Li
Zhang Yi
Jian Cheng Lv
Publikationsdatum
01.08.2014
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 2/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-013-1506-8

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