Title :
Support vector survival regression
Author_Institution :
Dept. of Clinical Eng., R. Liverpool Univ. Hosp., Liverpool
Abstract :
In this paper we show how the survival analysis problem can be formulated in terms of support vector regression, even in cases of censored observations. We prove bounds on the estimation error and we deduce that censoring is a limiting factor in the accuracy of solutions, although the convergence rate is of the same order as for uncensored observations.
Keywords :
medical computing; regression analysis; support vector machines; censoring; convergence; estimation error; support vector regression; survival analysis; Survival analysis; censored data; statistical learning theory; support vector machines;
Conference_Titel :
Advances in Medical, Signal and Information Processing, 2008. MEDSIP 2008. 4th IET International Conference on
Conference_Location :
Santa Margherita Ligure
Print_ISBN :
978-0-86341-934-8
