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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| Auteurs principaux: | , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
MDPI AG
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/add5c84becaa4f53811e8bb6d2edb647 |
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