Nesryne Mejri

An Insight on Evaluation Metrics Under the Imbalanced Case of Anomaly Detection

Romain Hermary, Nesryne Mejri, Djamila Aouada

Anomaly detection is inherently characterised by severe class imbalance, making the interpretation of evaluation metrics challenging. Although metrics such as AUROC, AUPR, F1-score, and MCC are widely used, their values convey different meanings depending on the anomaly ratio. In…Read more