Fig. 5

ROC curves comparison with the imbalanced database for ML models. The figure shows the ROC Curve and AUC for different binary classification algorithms applied to a PEFC data set. The algorithms evaluated include LR, SVM, KNN, DT, RF, and NB. The AUC is a measure of a model's ability to distinguish between the "Healthy" and "Faulty" classes. An AUC of 1 indicates perfect performance, while an AUC of 0.5 indicates random performance