Censoring Unbiased Regression Trees and Ensembles

DOI10.1080/01621459.2017.1407775zbMath1478.62289OpenAlexW2561265960WikidataQ92695870 ScholiaQ92695870MaRDI QIDQ5229919

Liqun Diao, Robert L. Strawderman, Jon Arni Steingrimsson

Publication date: 19 August 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/jhubiostat/paper282

zbMATH Keywords

random forestsrisk predictionloss estimationclassification and regression trees (CART)doubly robust

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05) Censored data models (62N01)

Related Items (7)

The Impact of Churn on Client Value in Health Insurance, Evaluation Using a Random Forest Under Various Censoring Mechanisms ⋮ Consistency of survival tree and forest models: splitting bias and correction ⋮ ROC‐guided survival trees and ensembles ⋮ Dynamic risk prediction triggered by intermediate events using survival tree ensembles ⋮ Unnamed Item ⋮ Interval Censored Recursive Forests ⋮ Unnamed Item

Uses Software

• rpart
• party
• partDSA
• randomSurvivalForest
• randomForest
• randomForestSRC

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bagging predictors
• Random survival forests
• Regression analysis with randomly right-censored data
• Exchangeably weighted bootstraps of the general empirical process
• Tree-based multivariate regression and density estimation with right-censored data
• The effect of splitting on random forests
• Semiparametric theory and missing data.
• Consistency of random forests
• Survival ensembles
• Regression Trees for Censored Data
• Linear Models, Random Censoring and Synthetic Data
• Linear regression with censored data
• Censored Regression: Local Linear Approximations and Their Applications
• A Partitioning Deletion/Substitution/Addition Algorithm for Creating Survival Risk Groups
• Recursively Imputed Survival Trees
• High-Dimensional Variable Selection for Survival Data
• Survival Trees by Goodness of Split
• A Doubly Robust Censoring Unbiased Transformation
• Random forests

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