Parameter C Optimizing for Robust ε-Support Vector Regression

Yuan Lv; Zhong Gan

doi:10.4028/www.scientific.net/AMM.543-547.2045

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547Parameter C Optimizing for Robust ε-Support Vector...

Parameter C Optimizing for Robust ε-Support Vector Regression

Abstract:

In case of experimental data contaminated with errors and noise, the robust ε-support vector regression has good forecast accuracy and high generalization ability. However, it depends on the selection of system parameter. Firstly, this paper introduces the robust ε-support vector regression method. Secondly, as the experiments prove, the new method achieves high forecast accuracy by virtue of the optimal penalty parameter C. Finally, the optimal method of parameter C is presented in the last section.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

2045-2048

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.2045

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Online since:

March 2014

Authors:

Yuan Lv*, Zhong Gan

Keywords:

Optimization, Penalty Parameter c, Robust ε-Support Vector Regression

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* - Corresponding Author

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