title: Rotation survival forest for right censored data.
abstract: Recently, survival ensembles have found more and more applications in biological and medical research when censored time-to-event data are often confronted. In this research, we investigate the plausibility of extending a rotation forest, originally proposed for classification purpose, to survival analysis. Supported by the proper statistical analysis, we show that rotation survival forests are able to outperform the state-of-art survival ensembles on right censored data. We also provide a C-index based variable importance measure for evaluating covariates in censored survival data.
authors.affiliation: School of Mathematics and Statistics, Central South University , China.
authors.forename: Lifeng
authors.initials: L
authors.lastname: Zhou
authors.affiliation: School of Mathematics and Statistics, Central South University , China.
authors.forename: Qingsong
authors.initials: Q
authors.lastname: Xu
authors.affiliation: School of Mathematics and Statistics, Central South University , China.
authors.forename: Hong
authors.initials: H
authors.lastname: Wang
keywords: Censored data; Medical decision making; Survival analysis; Survival ensemble