Table 7.

F1-scores of classifiers of the most important features across all of the datasets and associated area under the curve values for random forest (M ± S.D.).

Random forest	0.827
(AUC values)	(0.83 ± 0.23)
Adaboost	0.815
SVM	0.730
CART	0.762
MLP	0.625
Gaussian naive bayes	0.731

AUC, area under the curve; CART, classification and regression trees; MLP, multilayer perceptron; SVM, support vector machine.