https://github.com/slundberg/shap

A game theoretic approach to explain the output of any machine learning model.
https://github.com/slundberg/shap

deep-learning explainability gradient-boosting interpretability machine-learning shap shapley

Last synced: 5 months ago
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A game theoretic approach to explain the output of any machine learning model.

• Host: GitHub
• URL: https://github.com/slundberg/shap
• Owner: shap
• License: mit
• Created: 2016-11-22T19:17:08.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2025-06-25T20:02:53.000Z (5 months ago)
• Last Synced: 2025-06-25T21:19:30.119Z (5 months ago)
• Topics: deep-learning, explainability, gradient-boosting, interpretability, machine-learning, shap, shapley
• Language: Jupyter Notebook
• Homepage: https://shap.readthedocs.io
• Size: 279 MB
• Stars: 24,039
• Watchers: 245
• Forks: 3,385
• Open Issues: 701
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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