A Model-Agnostic Algorithm for Bayes Error Determination in Binary Classification

This paper presents the intrinsic limit determination algorithm (ILD Algorithm), a novel technique to determine the best possible performance, measured in terms of the AUC (area under the ROC curve) and accuracy, that can be obtained from a specific dataset in a binary classification problem with ca...

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Autores principales: Umberto Michelucci, Michela Sperti, Dario Piga, Francesca Venturini, Marco A. Deriu
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/add5c84becaa4f53811e8bb6d2edb647
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