Asymmetric Error Control Under Imperfect Supervision: A Label-Noise-Adjusted Neyman–Pearson Umbrella Algorithm

DOI10.1080/01621459.2021.2016423arXiv2112.00314OpenAlexW3215164748MaRDI QIDQ6077576

Xin Tong, Unnamed Author, Gareth M. James, Unnamed Author

Publication date: 18 October 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2112.00314

zbMATH Keywords

classificationtype I errorlabel noiseNeyman-Pearson (NP) paradigmumbrella algorithm

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data

Cites Work

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• Neyman-Pearson classification: parametrics and sample size requirement
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