Metric	Naive Bayes	Logistic Regression	Random Forest	adaBoost	Classification Tree	Light GBM	XGBoost
Acc	0.84	0.91	0.90	0.83	0.81	0.88	0.93
Sens	0.86	0.97	0.94	0.88	0.86	0.93	0.95
Spec	0.83	0.84	0.84	0.79	0.77	0.85	0.90
Prec	0.80	0.88	0.87	0.77	0.75	0.83	0.89
F1	0.83	0.92	0.91	0.82	0.80	0.88	0.92
MCC	0.68	0.82	0.79	0.67	0.62	0.77	0.85
AUC	0.84	0.91	0.89	0.83	0.81	0.89	0.93
AUPRC	0.84	0.91	0.88	0.85	0.82	0.90	0.94
TP	36.00	35.00	34.00	37.00	36.00	39.00	40.00
FP	6.00	1.00	2.00	5.00	6.00	3.00	2.00
FN	9.00	5.00	5.00	11.00	12.00	8.00	5.00
TN	43.00	26.00	26.00	41.00	40.00	44.00	47.00
*Note: The Logistic Regression and Random Forest model removes missing values from its final results and cannot be adequately compared with the other results.
†MCC: Matthew’s Correlation Coefficient AUC: Area Under the Curve AUPRC: Area Under the Precision Recall Curve TP: True Positive — FP: False Positive — FN: False Negative — TN: True Negative