Table 1.

Performance evaluations for different machine learning-incorporated genetic algorithm (GA) models on the GBM dataset.

Classifiers	No. of features	Sensitivity	Specificity	Accuracy
GA-RF	18	0.894	0.966	0.925
GA-XGB	18	0.889	0.88	0.889
GA-SVM	14	0.720	0.454	0.678

RF random forest, XGB XGBoost, SVM support vector machine.

Model with the best performance is indicated in bold font.