Table 3 Key hyperparameters for target classifiers and regressors
Target Domain | Model Type | Hyperparameters |
|---|---|---|
Job Status | DecisionTree (Clf) | class_weight: balanced |
criterion: gini | ||
max_depth: None | ||
min_samples_split: 2 | ||
min_samples_leaf: 1 | ||
Extraction Difficulty | DecisionTree (Clf) | class_weight: balanced |
criterion: gini | ||
max_depth: None | ||
min_samples_split: 2 | ||
min_samples_leaf: 1 | ||
Total Diameter | RandomForest (Reg) | n_estimators: 100 |
criterion: squared_error | ||
max_depth: None | ||
min_samples_split: 2 | ||
min_samples_leaf: 1 | ||
bootstrap: True | ||
Max Diameter | RandomForest (Reg) | n_estimators: 100 |
criterion: squared_error | ||
max_depth: None | ||
min_samples_split: 2 | ||
min_samples_leaf: 1 | ||
bootstrap: True | ||
Void Counts | DecisionTree (Reg) | criterion: squared_error |
max_depth: None | ||
min_samples_split: 2 | ||
min_samples_leaf: 1 | ||
Total Void Volume | CatBoost (Reg) | iterations: 500 |
depth: 6 | ||
learning_rate: 0.1 | ||
loss: RMSE | ||
l2_leaf_reg: 3 | ||
bootstrap_type: MVS | ||
Max Void Volume | CatBoost (Reg) | iterations: 500 |
depth: 6 | ||
learning_rate: 0.1 | ||
loss: RMSE | ||
l2_leaf_reg: 3 | ||
bootstrap_type: MVS |