Table 4. Parameters of machine learning models.

Model and parameters		Values
RFa
n_estimators		150
criterion		“gini”
max_depth		None
min_samples_split		2
min_samples_leaf		1
max_features		“sqrt”
bootstrap		True
random_state		42
XGBoostb
n_estimators		150
learning_rate		0.1
max_depth		3
objective		“binary:logistic”
subsample		1.0
colsample_bytree		1.0
gamma		0
reg_alpha		0
reg_lambda		1
random_state		42
use_label_encoder		False
eval_metric		“logloss”
DTc
criterion		“gini”
max_depth		None
min_samples_split		2
min_samples_leaf		1
max_features		None
random_state		42

^aRF: random forest.

^bXGBoost: extreme gradient boosting.

^cDT: decision tree.