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: about 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 (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-09-11T04:19:26.000Z (over 1 year ago)
• Last Synced: 2024-04-21T02:03:21.657Z (9 months 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

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