The authors introduce predicted-weighted balanced accuracy (pBA), a utility-weighted evaluation metric that uses predicted subconcept posteriors to reduce bias from within-class heterogeneity in imbalanced data.
Krawczyk , Learning from imbalanced data: open challenges and future directions , Progress in Artificial Intelligence, 5 (2016), pp
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Correcting Performance Estimation Bias in Imbalanced Classification with Minority Subconcepts
The authors introduce predicted-weighted balanced accuracy (pBA), a utility-weighted evaluation metric that uses predicted subconcept posteriors to reduce bias from within-class heterogeneity in imbalanced data.