woodtapper 0.0.6

A Python toolbox for interpretable and explainable tree ensembles.

User-friendly and scalable Python package for tapping decision tree ensembles

WoodTapper is a Python toolbox for interpretable and explainable tree ensembles learning, fully compatible with the scikit-learn API. WoodTapper enables seamless integration of interpretable rule extraction into existing machine learning workflows. In addition, it introduces an example-based explanation module that links predictions to a small set of representative samples.

🌳 Installation

From TestPypi:

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ woodtapper

From Source: Clone the repository:

git clone [e-mail]:artefactory/mgs-grf.git

And install the required packages into your environment (conda, mamba or pip):

pip install -r requirements.txt

Then run the following command from the repository root directory :

pip install -e .[dev]

🚀 How to use WoodTapper

## RandomForestClassifier rules extraction
from extract_rules.extractors import SirusClassifier

SIRUS = SirusClassifier(n_estimators=1000,max_depth=2,
                          quantile=10,p0=0.01, random_state=0)
SIRUS.fit(X_train,y_train)
y_pred_sirus = SIRUS.predict(X_test)

🙏 Acknowledgements

This work was done through a partenership between Artefact Research Center and the Laboratoire de Probabilités Statistiques et Modélisation (LPSM) of Sorbonne University.

   

📜 Citation

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