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Two-step LS-SVR for censored regression

Bae, Jong-Sig    (Department of Mathematics, Sungkyunkwan University   ); Hwang, Chang-Ha    (Department of Statistics, Dankook University   ); Shim, Joo-Yong    (Department of Data Science, Inje University  );
  • 초록

    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.


  • 주제어

    Censored regression .   generalized cross validation function .   Kaplan-Meier estimator .   kernel function .   least squares support vector machine .   randomly right censoring.  

  • 참고문헌 (20)

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    5. Jin, Z., Lin, D. Y., Wei, L. J. and Ying, Z. L. (2003). Rank-based inference for the accelerated failure time model. Biometrika, 90, 341-353. 
    6. Kaplan, E. L. and Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53, 457-481. 
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    14. Smola, A. and Scholkopf, B. (1998). On a kernel-based method for pattern recognition, regression, approximation and operator inversion. Algorithmica, 22, 211-231. 
    15. Stute, W. (1993). Consistent estimation under random censorship when covariables are available. Journal of Multivariate Analysis, 45, 89=103. 
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    17. Vapnik, V. N. (1998). Statistical learning theory, Wiley, New York. 
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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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