Table 2.

Model performance for the 4 model types (DT, RF, ANN, and SVM), at baseline.

Model	Version	Train accuracy	Test accuracy	Test precision	Test recall	Test F1	Test AUC
DT	Baseline	1.0	0.75	0.70	0.73	0.71	0.749
RF	Baseline	1.0	0.81	0.85	0.67	0.75	0.865
ANN	Baseline	0.75	0.76	0.71	0.74	0.72	0.832
SVM	Baseline	0.67	0.66	0.69	0.37	0.48	0.735

Accuracy = (TP + TN)/(All cases); Precision = TP/(TP + FP); Recall = TP/(TP + FN); F1 = 2*((precision*recall)/(precision + recall)).

Abbreviations: ANN = artificial neural networks; DT = decision trees; FN = false negative; FP = false positive; RF = random forest; SVM = support vector machines; TN = true negative; TP = true positive.