Table 4.

Parameter settings of six supervised learning models

ID	Model	Parameters
1	RF	n_estimators = 1000
2	LR	C = 1.0
3	KNN	n_neighbors = 5
4	XGBoost	booster = gbtree, learning_rate = 0.3, max_depth = 6, min_child_weight = 1
5	AdaBoost	base_estimator = DecisionTreeClassifier, algorithm = SAMME, n_estimators = 350, learning_rate = 0.4
6	GBDT	learning_rate = 0.1, n_estimators = 100, max_depth = 2, min_samples_split = 1.0, min_samples_leaf = 2