Anytime classification for a pool of instances

DOI10.1007/s10994-009-5118-6zbMath1473.62222OpenAlexW2002432783WikidataQ62833630 ScholiaQ62833630MaRDI QIDQ1959521

Geoffrey I. Webb, Bei Hui, Ying Yang

Publication date: 7 October 2010

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-009-5118-6

zbMATH Keywords

ensemble learninganytime classificationBayesian probabilistic classifierscomputational resource constraints

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• UCI-ml

Cites Work

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• Classifying under computational resource constraints: anytime classification using probabilistic estimators
• A model selection approach to signal denoising using Kullback's symmetric divergence
• Not so naive Bayes: Aggregating one-dependence estimators
• Boosting the margin: a new explanation for the effectiveness of voting methods
• On Information and Sufficiency
• A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
• An invariant form for the prior probability in estimation problems

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