Table 4.

Evaluation metrics.

Evaluation metrics	Logistic regression		Decision tree		Boosted trees		Random forest
	Mean (SD)	Minimum-maximum	Mean (SD)	Minimum-maximum	Mean (SD)	Minimum-maximum	Mean (SD)	Minimum-maximum
Accuracy	0.91 (0.007)	0.87-0.92	0.72 (0.03)	0.64-0.78	0.78 (0.04)	0.68-0.87	0.67 (0.05)	0.53-0.75
Precision	0.93 (0.01)	0.88-0.95	0.74 (0.04)	0.63-0.81	0.84 (0.06)	0.69-0.95	0.72 (0.11)	0.50-1.02
Recall/sensitivity	0.88 (0.01)	0.84-0.90	0.63 (0.05)	0.55-0.73	0.66 (0.06)	0.57-0.68	0.39 (0.07)	0.23-0.50
Specificity	0.94 (0.01)	0.90-0.96	0.80 (0.04)	0.72-0.88	0.84 (0.05)	0.78-0.98	0.88 (0.06)	0.80-1.04
F score	0.90 (0.01)	0.86-0.92	0.68 (0.03)	0.59-0.75	0.74 (0.05)	0.62-0.83	0.51 (0.05)	0.38-0.62
Area under receiver operating characteristic curve	0.96 (0.03)	0.91-0.99	0.66 (0.03)	0.61-0.71	0.84 (0.03)	0.79-0.89	0.71 (0.03)	0.69-0.79