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Robust support vector regression model in the presence of outliers and leverage points


Dhhan, Waleed and Midi, Habshah and Alameer, Thaera (2017) Robust support vector regression model in the presence of outliers and leverage points. Modern Applied Science, 11 (8). pp. 1913-1852. ISSN 1913-1844; ESSN: 1913-1852


Support vector regression is used to evaluate the linear and non-linear relationships among variables. Although it is non-parametric technique, it is still affected by outliers, because the possibility to select them as support vectors. In this article, we proposed a robust support vector regression for linear and nonlinear target functions. In order to carry out this goal, the support vector regression model with fixed parameters is used to detect and minimize the effects of abnormal points in the data set. The efficiency of the proposed method is investigated by using real and simulation examples.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Institute for Mathematical Research
DOI Number: https://doi.org/10.5539/mas.v11n8p92
Publisher: Canadian Center of Science and Education
Keywords: Robust regression; Support vector regression; Fixed parameters; Outliers; Leverage points
Depositing User: Mohd Hafiz Che Mahasan
Date Deposited: 16 Aug 2018 01:34
Last Modified: 19 Sep 2018 01:24
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.5539/mas.v11n8p92
URI: http://psasir.upm.edu.my/id/eprint/63148
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