A game theoretic approach to explain the output of any machine learning model.
created at Nov. 22, 2016, 7:17 p.m.
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🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
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Source code/webpage/demos for the What-If Tool
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XAI - An eXplainability toolbox for machine learning
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