Table 5.

The performance of each machine learning models.

Model	AUC	Accuracy	Sensitivity	Specificity	Precision	F-value	Yuden Index
LR	0.782	0.719	0.562	0.809	0.628	0.593	0.371
SVM	0.802	0.738	0.633	0.794	0.623	0.628	0.427
RF	0.798	0.746	0.632	0.802	0.615	0.623	0.434
MLP	0.794	0.728	0.605	0.793	0.610	0.608	0.398
XGBoost	0.808	0.749	0.724	0.762	0.632	0.675	0.486
DT	0.72	0.72	0.563	0.812	0.637	0.598	0.375
KNN	0.788	0.729	0.523	0.84	0.637	0.574	0.363
NBM	0.79	0.705	0.566	0.786	0.608	0.586	0.352