ROC and AUC with a binary predictor: a potentially misleading metric

DOI10.1007/S00357-019-09345-1OpenAlexW3104830070WikidataQ103724200 ScholiaQ103724200MaRDI QIDQ2220698

John III Muschelli

Publication date: 25 January 2021

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1903.04881

zbMATH Keywords

RAUCarea under the curveROC

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

Evaluating the informativity of a training sample for image classification by deep learning methods

Uses Software

• Unnamed Item
• ROCR
• Stata
• SAS
• Matplotlib
• Scikit
• pROC
• caTools
• Python
• GitHub
• reticulate
• fbroc

Cites Work

• The area above the ordinal dominance graph and the area below the receiver operating characteristic graph
• Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
• Unnamed Item

This page was built for publication: ROC and AUC with a binary predictor: a potentially misleading metric