Table 10.

Mean (SD) of the performance metrics for the male subjects’ classification models.

Algorithms	MAEa (years), mean (SD)	Accuracy, mean (SD)	RMSEb (years), mean (SD)	AUCc, mean (SD)	Precision, mean (SD)	Recall, mean (SD)
Decision tree	1.28 (0.13)	0.32 (0.03)	1.78 (0.17)	0.81 (0.02)	0.49 (0.06)	0.81 (0.11)
Random forest	1.04 (0.07)	0.34 (0.03)	1.44 (0.13)	0.85 (0.01)	0.57 (0.09)	0.73 (0.14)
Support vector machine	1.03 (0.09)	0.34 (0.03)	1.43 (0.08)	0.85 (0.01)	0.52 (0.09)	0.67 (0.12)
Multi-layer perceptron	0.98 (0.08)	0.33 (0.02)	1.32 (0.13)	0.84 (0.01)	0.65 (0.27)	0.61 (0.31)
K-nearest neighbor	1.16 (0.11)	0.30 (0.04)	1.57 (0.15)	0.82 (0.03)	0.59 (0.10)	0.59 (0.10)
Naïve bayes	1.07 (0.10)	0.29 (0.02)	1.39 (0.19)	0.81 (0.01)	0.57 (0.06)	0.58 (0.21)

^aMAE: mean absolute error.

^bRMSE: root mean squared error.

^cAUC: area under the curve.