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A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms
BACKGROUND: In classification and diagnostic testing, the receiver-operator characteristic (ROC) plot and the area under the ROC curve (AUC) describe how an adjustable threshold causes changes in two types of error: false positives and false negatives. Only part of the ROC curve and AUC are informat...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945414/ https://www.ncbi.nlm.nih.gov/pubmed/31906931 http://dx.doi.org/10.1186/s12911-019-1014-6 |