Table 2.

Results of k-fold, $K=5$, grid search cross validation for random forest classifier using multiple metric evaluation.

	Training			Test
	AUC	Precision	Accuracy	AUC	Precision	Accuracy
AUC	0.89	0.829	0.8478	0.54	0.25	0.848
Precision	0.77	0.391	0.8315	0.56	0.187	0.77
Accuracy	0.98	0.97	0.992	0.52	0.33	0.875

Each estimator is refitted using the best combination of hyperparameters. Random Forest is refitted using three scorers -AUC, precision, and accuracy- for either train and the test sets. In detail description of random forest fitting is given in the Supplementary Material.