Effect of pruning and early stopping on performance of a boosting ensemble.

DOI10.1016/S0167-9473(01)00067-6zbMath1072.62641MaRDI QIDQ5958472

Harris Drucker

Publication date: 3 March 2002

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

zbMATH Keywords

Neural networksBoostingDecision treesC4.5PruningPseudo-loss

Mathematics Subject Classification ID

Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (1)

Taxonomy for characterizing ensemble methods in classification tasks: a review and annotated bibliography

Uses Software

• UCI-ml
• C4.5

Cites Work

• Bagging predictors
• On the boosting ability of top-down decision tree learning algorithms
• Improved boosting algorithms using confidence-rated predictions
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