Table 2.

Comparison of the quality of the machine learning models.

Model	Accuracy	Precision	Recall	F1 score	Train time (s)	AUC-ROC
Random forest	0.842	0.836	0.842	0.837	0.718	0.947
Gradient boosting	0.815	0.805	0.815	0.801	1.988	0.932
K-nearest neighbors	0.813	0.806	0.813	0.808	0.003	0.910
Support vector machine	0.696	0.543	0.696	0.609	1.508	0.879
Logistic regression	0.751	0.714	0.751	0.707	0.058	0.827
Decision tree	0.813	0.815	0.813	0.814	0.017	0.832

AUC-ROC, area under the receiver operating characteristic curve.