Table 4.

Hyperparamter settings of supervised machine learning classifiers.

Model	Hyperparameter settings
RF	n_estimators=100, random_state=50, max_depth=300
AB	n_estimators=100, random_state=50
LR	random_state=50, solver=‘saga’,multi_class=‘ovr’,C=3.0
MLP	random_state=50, max_iter=200
GBM	n_estimators=100, learning_rate=1, random_state=50
ET	n_estimators=100, random_state=50, max_depth=300
KNN	n_neighbors=5

RF: Random Forest; LR: Logistic Regression; MLP: Multilayer Perceptron; GBM: Gradient Boosting Machine; AB: AdaBoost, kNN: k Nearest Neighbours; ET: Extra Tree Classifier.