Table 2.

Parameters stunning setting for the ML classification

ML Classifiers	Grid of parameters
Logistic Regression (LR)	penalty=’12’,
	C = 0.1,
	solver=’liblinear’,
	random_state = 1
K-Neighbours Classifier (KNN)	n_neighbors = 11, weights = “distance”,
	p = 2, metric=’manhattan’
Gaussian Naïve Bayes (GNB)	var_smoothing = 0.0002
Support Vector Machine (SVM),	C = 100, random_state = 1,
	gamma = 0.01, probability = True
EnsembleVoteClassifier	(clfs=[LR, KNN, GNB, SVM], weights=[1,1,1,1,1])

Cross validation = RepeatedStratifiedKFold(n_splits = 5, n_repeats = 3, random_state = 1)