| Hyperparameters | Value |
|---|---|
| aggressive_elimination | False |
| cv | 5 |
| error_score | nan |
| estimator__categorical_features | None |
| estimator__early_stopping | auto |
| estimator__l2_regularization | 0.0 |
| estimator__learning_rate | 0.1 |
| estimator__loss | log_loss |
| estimator__max_bins | 255 |
| estimator__max_depth | None |
| estimator__max_iter | 100 |
| estimator__max_leaf_nodes | 31 |
| estimator__min_samples_leaf | 20 |
| estimator__monotonic_cst | None |
| estimator__n_iter_no_change | 10 |
| estimator__random_state | None |
| estimator__scoring | loss |
| estimator__tol | 1e-07 |
| estimator__validation_fraction | 0.1 |
| estimator__verbose | 0 |
| estimator__warm_start | False |
| estimator | HistGradientBoostingClassifier() |
| factor | 3 |
| max_resources | auto |
| min_resources | exhaust |
| n_jobs | -1 |
| param_grid | {'max_leaf_nodes': [5, 10, 15], 'max_depth': [2, 5, 10]} |
| random_state | 42 |
| refit | True |
| resource | n_samples |
| return_train_score | True |
| scoring | None |
| verbose | 0 |
import pickle
with open(dtc_pkl_filename, 'rb') as file:
clf = pickle.load(file)
[More Information Needed]