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 |