A majorization-minimization scheme for L 2 support vector regression

In a support vector regression (SVR) model, using the squared ϵ-insensitive loss function makes the optimization problem strictly convex and yields a more concise solution. However, the formulation of -SVR leads to a quadratic programming which is expensive to solve. This paper reformulates the opti...

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Veröffentlicht in:	Journal of statistical computation and simulation Jg. 91; H. 15; S. 3087 - 3107
1. Verfasser:	Zheng, Songfeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Taylor & Francis 13.10.2021
Schlagworte:	majorization-minimization algorithm quadratic programming squared ϵ-insensitive loss function Support vector regression
ISSN:	0094-9655, 1563-5163
Online-Zugang:	Volltext
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