Improving the training time of support vector regression algorithms through novel hyper-parameters search space reductions-Reference-Cited by-同舟云学术

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Improving the training time of support vector regression algorithms through novel hyper-parameters search space reductions

Published:2009-10 Issue:16-18 Volume:72 Page:3683-3691
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Ortiz-García Emilio G.,Salcedo-Sanz Sancho,Pérez-Bellido Ángel M.,Portilla-Figueras Jose A.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference23 articles.

1. Statistical learning theory;Vapnik,1998

2. Support vector machines for wind speed prediction;Mohandes;Renewable Energy,2004

3. Support vector regression for the simultaneous learning of a multivariate function and its derivatives;Lázaro;Neurocomputing,2005

4. Model optimizing and feature selecting for support vector regression in time series forecasting;He;Neurocomputing,2008

5. River stage prediction based on a distributed support vector regression;Wu;Journal of Hydrology,2008

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