Table 13.

Mean (SD) of the performance metrics, for the female 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	1.31 (0.09)	0.28 (0.02)	1.78 (0.13)	0.80 (0.02)	0.56 (0.05)	0.82 (0.09)
Random forest	1.29 (0.10)	0.30 (0.03)	1.77 (0.10)	0.79 (0.02)	0.59 (0.13)	0.74 (0.17)
Support vector machine	1.21 (0.06)	0.32 (0.04)	1.68 (0.06)	0.80 (0.01)	0.55 (0.07)	0.71 (0.11)
Multi-layer perceptron	1.36 (0.24)	0.30 (0.02)	1.85 (0.37)	0.77 (0.02)	0.60 (0.11)	0.63 (0.22)
K-nearest neighbors	1.41 (0.12)	0.30 (0.02)	1.96 (0.12)	0.76 (0.03)	0.55 (0.07)	0.61 (0.18)
Naïve bayes	1.74 (0.23)	0.22 (0.02)	2.23 (0.27)	0.65 (0.03)	0.58 (0.06)	0.82 (0.09)

^aMAE: mean absolute error.

^bRMSE: root mean squared error.

^cAUC: area under the curve.