An empirical comparison of learning algorithms for nonparametric scoring: the \textsc{TreeRank} algorithm and other methods

DOI10.1007/s10044-012-0299-1zbMath1284.68495OpenAlexW2022319760MaRDI QIDQ2444590

Marine Depecker, Stéphan Clémençon, Nicolas Vayatis

Publication date: 10 April 2014

Published in: PAA. Pattern Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10044-012-0299-1

zbMATH Keywords

resamplingROC curveAUC maximizationscoring rulesranking treesfeature randomization

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Learning and adaptive systems in artificial intelligence (68T05) Graph theory (including graph drawing) in computer science (68R10)

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A review on instance ranking problems in statistical learning ⋮ Quantitative robustness of instance ranking problems ⋮ Asymptotic linear expansion of regularized M-estimators ⋮ The TreeRank Tournament algorithm for multipartite ranking ⋮ Elicitability of Instance and Object Ranking

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