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Kernel Ridge Regression with Randomly Right Censored Data
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 Title & Authors
Kernel Ridge Regression with Randomly Right Censored Data
Shim, Joo-Yong; Seok, Kyung-Ha;
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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.
Generalized cross validation function;kernel ridge regression;randomly right censoring;iterative reweighted least squares procedure;Kaplan-Meier estimator;
 Cited by
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