Why ROC-AUC Is Misleading for Highly Imbalanced Data: In-Depth Evaluation of MCC, F2-Score, H-Measure, and AUC-Based Metrics Across Diverse Classifiers

Technologies 2026 Open access

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Authors: Mehdi Imani, Majid Joudaki, Ayoub Bagheri, Hamid R. Arabnia

DOI: 10.3390/technologies14010054

Cited by: 7

References: 37

Abstract

This study re-evaluates ROC-AUC for binary classification under severe class imbalance (

Imbalanced Data Classification Techniques Financial Distress and Bankruptcy Prediction Explainable Artificial Intelligence (XAI)

References 37