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...

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Detalles Bibliográficos
Autores principales: Carrington, André M., Fieguth, Paul W., Qazi, Hammad, Holzinger, Andreas, Chen, Helen H., Mayr, Franz, Manuel, Douglas G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
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

Internet

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

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