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Reliable Bayesian Network Structure Learning in Biomedical Applications: Model Uncertainty Criterion and Its Operating Characteristics.

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第一作者： Grigoriy,Gogoshin

第一单位： Department of Computational and Quantitative Medicine, Beckman Research Institute, and Diabetes and Metabolism Research Institute, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, 91010, CA, USA.

作者： Grigoriy,Gogoshin ^[1] ; Andrei S,Rodin ^[2]

作者单位： Department of Computational and Quantitative Medicine, Beckman Research Institute, and Diabetes and Metabolism Research Institute, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, 91010, CA, USA. ^[1] Department of Computational and Quantitative Medicine, Beckman Research Institute, and Diabetes and Metabolism Research Institute, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, 91010, CA, USA.;Irell and Manella Graduate School of Biomedical Sciences, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, 91010, CA, USA. ^[2]

关键词 AIC APOE BD BDeu BIC Bayesian network K2 MDL MU conditional independence interpretable machine learning misclassification error model selection criteria probabilistic graphical model probabilistic network sampling error statistical uncertainty

DOI 10.1101/2025.10.13.681946

PMID 41280097

发布时间 2025-11-27

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Reliable Bayesian Network Structure Learning in Biomedical Applications: Model Uncertainty Criterion and Its Operating Characteristics.

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Reliable Bayesian Network Structure Learning in Biomedical Applications: Model Uncertainty Criterion and Its Operating Characteristics.

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