Concept learning using complexity regularization

DOI10.1109/18.481777zbMath0844.62006OpenAlexW2120337009MaRDI QIDQ4879989

Kenneth Zeger, Gábor Lugosi

Publication date: 1 September 1996

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/18.481777

zbMATH Keywords

classificationpattern recognitionlearning theoryBayes error probabilityapproximation errorBayes ruleestimation errorcomplexity regularizationinfinite Vapnis Chervonenkis dimension

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Statistical aspects of information-theoretic topics (62B10)

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Sampling and empirical risk minimization ⋮ A penalized criterion for variable selection in classification ⋮ Model selection by bootstrap penalization for classification ⋮ Adaptive partitioning schemes for bipartite ranking ⋮ Multiclass classification with potential function rules: margin distribution and generalization ⋮ On learning multicategory classification with sample queries. ⋮ Model selection in utility-maximizing binary prediction ⋮ Theory of Classification: a Survey of Some Recent Advances ⋮ Estimation of the conditional risk in classification: the swapping method

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