Table 5.

Best hyperparameters selected to be fed into the classifiers

Num	ML Models	Hyper-parameters	F1-score
1	HGB classifier	(‘verbose’:2,’random_state’:999,’n_estimators’:14,’max_deph’:7’criterion’: gini’)	81.32
4	SVM (kernel = RBF)	C = 15, G = 0.004	76.14
5	XG Boost Classifier	‘min_chid_weigh’ = 1’max_depht’ = 16,’learning_rate’ = 0.4, ‘gamma’ = 0.1, ‘colsample_bytree’ = 0.4	83.7