. 2023 Feb 13;9(2):e13692. doi: 10.1016/j.heliyon.2023.e13692

Table 2.

Overall classification performance for each model.

Model	Precision	Recall	F1 score	Accuracy
ERT	0.505 $\pm$ 0.125	0.522 $\pm$ 0.139	0.498 $\pm$ 0.129	0.511 $\pm$ 0.121
XGBoost	0.394 $\pm$ 0.064	0.436 $\pm$ 0.078	0.374 $\pm$ 0.077	0.397 $\pm$ 0.067
SVM (RBF)	0.475 $\pm$ 0.066	0.482 $\pm$ 0.062	0.467 $\pm$ 0.070	0.489 $\pm$ 0.067
SVM(Linear)	0.441 $\pm$ 0.087	0.514 $\pm$ 0.109	0.420 $\pm$ 0.092	0.455 $\pm$ 0.085
Mlogit	0.464 $\pm$ 0.061	0.446 $\pm$ 0.061	0.422 $\pm$ 0.049	0.466 $\pm$ 0.067

Mean $\pm$ SD. ERT, extremely randomized trees; XGBoost, extreme gradient boosting; SVM, support vector machine; Mlogit, multinomial logistic regression.