Computing AIC for black-box models using generalized degrees of freedom: A comparison with cross-validation

DOI10.1080/03610918.2017.1315728OpenAlexW2963436583WikidataQ57019711 ScholiaQ57019711MaRDI QIDQ5084925

Severin Hauenstein, Carsten F. Dormann, Simon N. Wood

Publication date: 29 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.02743

zbMATH Keywords

random forestmodel complexitydata perturbationboosted regression trees

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• CRAN
• MASS (R)
• gbm
• randomForest
• ElemStatLearn
• gamair

Cites Work

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• Evaluation of the Kullback‐Leibler Discrepancy for Model Selection in Open Population Capture‐Recapture Models
• Core Statistics
• Optimal Model Assessment, Selection, and Combination
• On Information and Sufficiency

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