Aggregating classifiers with mathematical programming

DOI10.1016/j.csda.2003.11.015zbMath1429.62230OpenAlexW2035049899MaRDI QIDQ957061

Willy Gochet, Jan Adem

Publication date: 26 November 2008

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

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/118333

zbMATH Keywords

mathematical programmingcomputational efficiencybaggingboostingsupervised classification

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of mathematical programming (90C90)

Related Items (3)

Counting and enumerating aggregate classifiers ⋮ Using boosting to prune double-bagging ensembles ⋮ Taxonomy for characterizing ensemble methods in classification tasks: a review and annotated bibliography

Uses Software

• UCI-ml
• LINDO
• SAS

Cites Work

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• Bagging predictors
• Latent class models for classification
• Multilayer statistical classifiers
• Using \(k\)-nearest-neighbor classification in the leaves of a tree
• Dimension reduction techniques and the classification of bent double galaxies
• Credit Scoring and Its Applications
• Multigroup Discriminant Analysis Using Linear Programming

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