Table 3.

Comparison of evaluation effects of different evaluation models.

Model	Index p OR(95%CI)
	Accuracy	Classification Error	Precision	Recall	F1_Score	Auc
Random forest	0.9344	0.0655	0.9040	0.8967	0.9003	0.9713
Logistics regression	0.9172	0.0827	0.8747	0.8747	0.8747	0.9478
Navie Bayesian	0.8234	0.1765	0.6690	0.9219	0.7753	0.9378
GBDT	0.9083	0.0916	0.8610	0.8617	0.8613	0.9520
KNN	0.9221	0.0778	0.8754	0.8912	0.8832	0.9579