Weighted LS-SVM Regression for Right Censored Data
Daehak Kim, Hyeong-Chul Jeong · Communications for Statistical Applications and Methods · 2006
In this paper we propose an estimation method on the regression model with randomly censored observations of the training data set. The weighted least squares support vector machine regression is applied for the regression function estimation by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed estimation method.