April 29, 2024, 4:45 a.m. | Ariane Cwiling (MAP5 - UMR 8145), Vittorio Perduca (MAP5 - UMR 8145), Olivier Bouaziz (MAP5 - UMR 8145)

stat.ML updates on arXiv.org arxiv.org

arXiv:2404.17211v1 Announce Type: cross
Abstract: In the context of right-censored data, we study the problem of predicting the restricted time to event based on a set of covariates. Under a quadratic loss, this problem is equivalent to estimating the conditional Restricted Mean Survival Time (RMST). To that aim, we propose a flexible and easy-to-use ensemble algorithm that combines pseudo-observations and super learner. The classical theoretical results of the super learner are extended to right-censored data, using a new definition of …

abstract arxiv context data event loss math.st mean set stat.me stat.ml stat.th study survival type

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