Research of mapped least squares SVM optimal configuration

Abstract

To determine the optimal configuration of the kernel parameters, the physical characteristic of the mapped least squares (LS) support vector machine (SVM) is investigated by analyzing the frequency responses of the filters deduced from the support value and LS-SVM itself. This analysis of the mapped LS-SVM with Gaussian kernel illustrates that the optimal configuration of the kernel parameter exists and the regulation constant is directly determined by the frequency content of the image. The image regression estimation experiments demonstrate the effectiveness of the presented method. © 2006 Springer.