Table 2.

Performance of machine learning models.

Model	Accuracy	AUC	Recall	Precision	F1 score
XGBoost classifier	0.725	0.705	0.718	0.688	0.686
Random forest classifier	0.734	0.722	0.728	0.735	0.652
Decision tree classifier	0.606	0.675	0.675	0.725	0.713
CatBoost classifier	0.732	0.752	0.725	0.703	0.695
Support vector classifier	0.659	0.631	0.665	0.717	0.673
Logistics regression	0.635	0.666	0.625	0.684	0.650

AUC: receiver operating characteristic curve.