Fig. 3

The AUC comparison of six machine learning models. (a) RF model, AUC = 0.850; (b) AdaBoost model, AUC = 0.655; (c) SVM model, AUC = 0.677; (d) DT model, AUC = 0.712; (e) KNN model, AUC = 0.677; (f) LD, AUC = 0.777

Abbreviations: EPDS, Edinburgh Postnatal Depression Scale; AUC, area under the curve; RF, random forest; AdaBoost, adaptive boosting; SVM, support vector machine; DT, decision tree; KNN, k-nearest neighbors; LD, linear discriminant

Note: Normal (0 < EPDS ≤ 9), Abnormal (EPDS ≥ 10)