https://github.com/mpolinowski/sklearn-model-explainability
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model.
https://github.com/mpolinowski/sklearn-model-explainability
explainable-ml ml-models shap sklearn
Last synced: 2 months ago
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SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model.
- Host: GitHub
- URL: https://github.com/mpolinowski/sklearn-model-explainability
- Owner: mpolinowski
- Created: 2023-09-11T04:19:22.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2023-09-11T04:19:26.000Z (almost 3 years ago)
- Last Synced: 2025-01-28T19:17:27.268Z (over 1 year ago)
- Topics: explainable-ml, ml-models, shap, sklearn
- Language: Jupyter Notebook
- Homepage: https://mpolinowski.github.io/docs/IoT-and-Machine-Learning/ML/2023-09-10--model-explainability-shap/2023-09-11
- Size: 1.37 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0