Table 1. Optimal parameters for each machine learning model are selected through the grid search.

Model	Optimal parameters
LR	Penalty: ‘l2,’ C: 0.1
SVM	C: 0.1, gamma: 0.01, kernel: ‘rbf’
RF	n_estimators: 3000, max depth: 5, min samples leaf: 4, min samples split: 10
ANN	Optimizer: ‘Adam’, learning rate: 0.0001, batch size: 200, epoch: 60
XGB	n_estimators: 5000, learning rate: 0.05, colsample bytree: 0.3, max depth: 4, gamma: 1, lambda: 0.5, alpha: 0.5