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Kernel Ridge Regression with Randomly Right Censored Data

  • Shim, Joo-Yong (Department of Applied Statistics, Catholic University of Daegu) ;
  • Seok, Kyung-Ha (Institute of Statistical Information, Department of Data Science, Inje University)
  • Published : 2008.03.30

Abstract

This paper deals with the estimations of kernel ridge regression when the responses are subject to randomly right censoring. The iterative reweighted least squares(IRWLS) procedure is employed to treat censored observations. The hyperparameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation(GCV) function. Experimental results are then presented which indicate the performance of the proposed procedure.

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