Table 2.

Output classification metrics of classification accuracy, AUC of the receiver operating curve, precision, and recall for the various machine-learning approaches

Method	AUC	CA	F1	Precision	Recall
Random Forest	0.927	0.875	0.875	0.878	0.875
k-Nearest Neighbor	0.914	0.812	0.812	0.813	0.812
Decision Tree	0.886	0.812	0.812	0.815	0.812
Neural Network	0.798	0.76	0.757	0.775	0.76
Naive Bayes	0.756	0.667	0.659	0.682	0.667
Logistic regression	0.778	0.656	0.652	0.665	0.656