Estimation of regression parameters using SVM with new methods for meta parameter

Abstract

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In this article, we propose two methods for selection of meta parameter (C) in support vector regression. The proposed methods are robust because these are based on the robust statistical measures. The performance of the proposed parameter selection methods is evaluated in case of normal and non-normal distributed error variables. It is evaluated in the sense of prediction risk and mean square error of estimates of regression parameters for clean and outlier data.