Mitochondrial mt12361A>G increased risk of metabolic dysfunction-associated steatotic liver disease among non-diabetes

Table 6 Performance of the artificial intelligence models

Algorithm	AUC	Accuracy	F1	Precision	Recall
Training
Random forest	1.000	1.000	1.000	1.000	1.000
XGBoost	0.970	0.918	0.918	0.919	0.918
Naive Bayes	0.824	0.747	0.748	0.757	0.747
Logistic regression	0.817	0.745	0.744	0.744	0.745
Validation
Random forest	0.876	0.802	0.803	0.807	0.802
XGBoost	0.861	0.763	0.764	0.767	0.763
Naive Bayes	0.849	0.776	0.777	0.786	0.776
Logistic regression	0.853	0.756	0.754	0.754	0.756

AUC: Area under curve; XGBoost: eXtreme gradient boosting.