A fast iterative single data approach to training unconstrained least squares support vector machines

Least squares support vector machines (LS-SVMs) express the training in terms of solving a system of linear equations or an equivalent quadratic program (QP) with one linear equality constraint, in contrast to a QP with lower and upper bounds and one linear equality constraint for conventional suppo...

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Veröffentlicht in:Neurocomputing (Amsterdam) 2013-09, Vol.115, p.31-38
Hauptverfasser: Li, Bing, Song, Shiji, Li, Kang
Format: Artikel
Sprache:eng
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