表 2.

四种模型在测试集上的性能表现

Performance of the 4 models on the test set

Indicator	LR	Naive bayes	RF	EBM
LR: Logistic regression; RF: Random forest; EBM: Explainable boosting machine; AUC: Area under the subject's working characteristic curve.
AUC (95%CI)	0.807 (0.773-0.836)	0.785 (0.755-0.813)	0.838 (0.810-0.870)	0.857 (0.831-0.887)
Accuracy	0.789	0.747	0.787	0.808
Precision	0.671	0.580	0.734	0.733
Recall	0.766	0.471	0.420	0.536
F1-score	0.488	0.520	0.535	0.619
Brier score	0.158	0.200	0.148	0.135