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Random Survival Forest×Nelson-Aalen Estimator for Kumulativ Risikofunktion×
FagområdeOverlevelsesanalyseOverlevelsesanalyse
FamilieSurvival analysisSurvival analysis
Oprindelsesår20081972
OphavspersonIshwaran, H., Kogalur, U.B., Blackstone, E.H. & Lauer, M.S.Wayne Nelson & Odd Aalen
TypeEnsemble machine learning survival modelNon-parametric cumulative hazard estimator
Oprindelig kildeIshwaran, H., Kogalur, U.B., Blackstone, E.H. & Lauer, M.S. (2008). Random Survival Forests. Annals of Applied Statistics, 2(3), 841–860. DOI ↗Nelson, W. (1972). Theory and applications of hazard plotting for censored failure data. Technometrics, 14(4), 945–966. DOI ↗
AliasserRSF, Rastgele Sağkalım Ormanı (RSF), survival random forestNelson-Aalen cumulative hazard, Aalen estimator, empirical cumulative hazard, Nelson-Aalen kümülatif hazard tahmincisi
Relaterede25
ResuméRandom Survival Forest (RSF), introduced by Ishwaran, Kogalur, Blackstone, and Lauer in 2008, is an ensemble machine learning method that adapts the Random Forest algorithm to time-to-event (survival) data. Trees are grown using log-rank splitting to handle censored observations naturally, and the ensemble aggregates cumulative hazard functions across hundreds of trees to produce predictions and variable importance rankings.The Nelson-Aalen estimator is a non-parametric estimator of the cumulative hazard function from right-censored time-to-event data. Developed by Wayne Nelson for reliability hazard plotting in 1972 and placed on a rigorous counting-process foundation by Odd Aalen in 1978, it accumulates the ratio of observed events to the number at risk at each event time, providing the natural hazard-scale companion to the Kaplan-Meier survival curve.
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ScholarGateSammenlign metoder: Random Survival Forest · Nelson-Aalen Estimator. Hentet 2026-06-19 fra https://scholargate.app/da/compare