TABLE 15.

Combined features: performance and hyperparameters of ML models.

Model	Train_Acc	Val_Acc	Test_Acc	Train_F1	Val_F1	Test_F1	Hyperparameters
XGBoost	99.99	98.7	98.56	0.99	0.9832	0.9813	gamma=0.073,learning_rate=0.2459, max_depth=10, estimators=171, reg_alpha=0.2, reg_lambda=0.3
Random Forest	99.83	96.76	96.41	0.9979	0.9579	0.95328	min_samples_leaf=1, min_samples_split=9, estimators=112,max_depth=30
LightGBM	99.76	98.25	98.21	0.9969	0.9774	0.9768	lr=0.313, max_depth= 23, min_child_samples=12, num_leaves=46,max_depth= 23
Extra Trees	99.35	96.33	95.8	0.9916	0.9528	0.9461	min_samples_leaf=1, min_samples_split=3, estimators=100, max_depth=20