Parameter Tuning in Support Vector Regression using Ensemble Learning

Abstract

In support vector regression, the value of parameters included in kernels affects strongly generalization ability: it is often difficult to determine appropriate values of those parameters in advance. In this paper, we clarify that the burden for deciding the value of those parameters in support vector regression can be reduced by utilizing ensemble learning.