shap/shap
shap
A game theoretic approach to explain the output of any machine learning model.
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shap
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Nov 22, 2016
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SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. The library provides a unified framework for interpreting predictions from any machine learning model.
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Updated 1 months ago
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- Project created
- Nov 22, 2016
- Forked
- Mar 22, 2026
- Your last push
- 1 months ago
- Upstream last push
- 7 days ago
- Tracked since
- Mar 12, 2026
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