Table 3.

Results of the training sets using five machine learning algorithms.

model	accuracy	precision	recall	f1	auc_pr	auc_roc
Logistic regression	0.6376	0.5693	0.6145	0.5910	0.3864	0.7025
Random forest	0.8119	0.7027	0.7719	0.7357	0.6621	0.8854
Support vector machine	0.6789	0.5829	0.6291	0.6051	0.4513	0.7480
KNN	0.8486	0.7754	0.6073	0.6811	0.6197	0.8702
XGBoost	0.9954	0.9972	0.9868	0.9920	0.9993	0.9999