Table 1.

Comparison of the random forest classifier (RF), logistic regression (LR), and support vector classification (SVC) models for the 9 output classifications using k-fold (n = 5).

	RF	LR	SVC
Accuracy	0.823 ± 0.060	0.732 ± 0.046	0.677 ± 0.049
F1 score	0.806 ± 0.076	0.654 ± 0.044	0.568 ± 0.086
Recall	0.790 ± 0.077	0.660 ± 0.031	0.562 ± 0.072
Precision	0.865 ± 0.072	0.692 ± 0.050	0.629 ± 0.109