Table 4.

Results of the testing sets using five machine learning algorithms.

model	accuracy	precision	recall	f1	auc_pr	auc_roc
Logistic regression	0.6727	0.5713	0.6056	0.5879	0.2947	0.6311
Random forest	0.6909	0.5583	0.5778	0.5679	0.3208	0.6311
Support vector machine	0.6545	0.5621	0.5944	0.5778	0.2766	0.6644
KNN	0.7818	0.5850	0.5556	0.5699	0.2594	0.4867
XGBoost	0.7818	0.5850	0.5556	0.5699	0.2924	0.6800