Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 11, Number 1 (2017), 532-569.
Support vector regression for right censored data
We develop a unified approach for classification and regression support vector machines for when the responses are subject to right censoring. We provide finite sample bounds on the generalization error of the algorithm, prove risk consistency for a wide class of probability measures, and study the associated learning rates. We apply the general methodology to estimation of the (truncated) mean, median, quantiles, and for classification problems. We present a simulation study that demonstrates the performance of the proposed approach.
Electron. J. Statist., Volume 11, Number 1 (2017), 532-569.
Received: February 2016
First available in Project Euclid: 2 March 2017
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Goldberg, Yair; Kosorok, Michael R. Support vector regression for right censored data. Electron. J. Statist. 11 (2017), no. 1, 532--569. doi:10.1214/17-EJS1231. https://projecteuclid.org/euclid.ejs/1488423807
- Matlab code. Please read the file README.pdf for details on the files in this folder.