Fig. 7
A comparison of ROC curves and AUC values shows the predict CSA practice for mushroom production. These comparisons were made for nine different ML algorithms using SMOTE, repeated stratified 10-fold CV with hyperparameter. For ROC curve, which compares true positive rate (sensitivity against the false positive rate across different thresholds to evaluate algorithm performance. The AUC, ranging from 0 (random guessing) to 1 (excellent performance), quantifies overall discriminative ability.
