Consistency of Random Survival Forests

dc.creatorIshwaran, Hemant
dc.creatorKogalur, Udaya B.
dc.date2008-11-18
dc.date.accessioned2026-07-07T10:19:08Z
dc.date.available2026-07-07T10:19:08Z
dc.descriptionWe prove uniform consistency of Random Survival Forests (RSF), a newly introduced forest ensemble learner for analysis of right-censored survival data. Consistency is proven under general splitting rules, bootstrapping, and random selection of variables--that is, under true implementation of the methodology. A key assumption made is that all variables are factors. Although this assumes that the feature space has finite cardinality, in practice the space can be a extremely large--indeed, current computational procedures do not properly deal with this setting. An indirect consequence of this work is the introduction of new computational methodology for dealing with factors with unlimited number of labels.
dc.descriptionSubmitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0811.2844
dc.identifierhttp://arxiv.org/abs/0811.2844
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/174400
dc.subjectStatistics Theory
dc.titleConsistency of Random Survival Forests
dc.typetext

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