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논문 상세정보

Abstract

This paper deals with the estimations of the least squares support vector regression when the responses are subject to randomly right censoring. The estimation is performed via two steps - the ordinary least squares support vector regression and the least squares support vector regression with censored data. We use the empirical fact that the estimated regression functions subject to randomly right censoring are close to the true regression functions than the observed failure times subject to randomly right censoring. The hyper-parameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation function. Experimental results are then presented which indicate the performance of the proposed procedure.

참고문헌 (20)

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  20. Zhou, M. (1992). M-estimation in censored linear models. Biometrika, 79, 837-841. 

이 논문을 인용한 문헌 (1)

  1. 2013. "" Journal of the Korean Data & Information Science Society = 한국데이터정보과학회지, 24(3): 625~636 

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