Instructions to use gusdelact/penguins-decision-tree with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use gusdelact/penguins-decision-tree with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("gusdelact/penguins-decision-tree", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
| { | |
| "design_doc": "notes/02_design_modeling.md", | |
| "estimator": "DecisionTreeClassifier", | |
| "model_type": "decision_tree_classifier", | |
| "trained_at": "2026-05-18T14:31:31.534278", | |
| "training_seconds": 4.203144073486328, | |
| "random_state": 42, | |
| "features": [ | |
| "Culmen Length (mm)", | |
| "Culmen Depth (mm)", | |
| "Flipper Length (mm)", | |
| "Body Mass (g)", | |
| "Island_Biscoe", | |
| "Island_Dream", | |
| "Island_Torgersen", | |
| "Sex_FEMALE", | |
| "Sex_MALE", | |
| "Clutch Completion_No", | |
| "Clutch Completion_Yes" | |
| ], | |
| "target": "Species", | |
| "n_samples_train": 258, | |
| "n_features": 11, | |
| "search_strategy": "GridSearchCV", | |
| "cv_folds": 5, | |
| "scoring": "f1_weighted", | |
| "param_grid": { | |
| "max_depth": [ | |
| 3, | |
| 4, | |
| 5, | |
| 6, | |
| 8, | |
| 10, | |
| null | |
| ], | |
| "min_samples_split": [ | |
| 2, | |
| 5, | |
| 10 | |
| ], | |
| "min_samples_leaf": [ | |
| 1, | |
| 2, | |
| 5 | |
| ], | |
| "criterion": [ | |
| "gini", | |
| "entropy" | |
| ] | |
| }, | |
| "best_params": { | |
| "criterion": "gini", | |
| "max_depth": 5, | |
| "min_samples_leaf": 1, | |
| "min_samples_split": 5 | |
| }, | |
| "params": { | |
| "criterion": "gini", | |
| "max_depth": 5, | |
| "min_samples_leaf": 1, | |
| "min_samples_split": 5 | |
| }, | |
| "best_cv_score": 0.973031605176191, | |
| "best_cv_score_std": 0.019704745060290966, | |
| "best_fold_scores": [ | |
| 0.9808021038790269, | |
| 0.9615384615384616, | |
| 0.9807921654969955, | |
| 0.9420252949664715, | |
| 1.0 | |
| ], | |
| "best_train_score_mean": 0.9932328656107854, | |
| "model_path": "models/model.joblib", | |
| "tree_depth": 5, | |
| "tree_n_leaves": 10 | |
| } |