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