Maximum a posteriori pruning on decision trees and its application to bootstrap bumping

DOI10.1016/j.csda.2004.09.010zbMath1431.62028OpenAlexW2007435156MaRDI QIDQ959196

Yongdai Kim, Jinseog Kim

Publication date: 11 December 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2004.09.010

zbMATH Keywords

cross-validationdecision treeBICposterior probabilitybumpingcost-complexity pruning

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian problems; characterization of Bayes procedures (62C10) Statistical aspects of information-theoretic topics (62B10)

Cites Work

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• Bagging predictors
• Inferring decision trees using the minimum description length principle
• Modeling by shortest data description
• Estimating the dimension of a model
• Characterization of the Bayes estimator and the MDL estimator for exponential families