shap by shap

A game theoretic approach to explain the output of any machine learning model.

updated at June 9, 2024, 8:48 a.m.

240 +0

21,926 +63

3,194 +11

what-if-tool by PAIR-code

Source code/webpage/demos for the What-If Tool

updated at June 8, 2024, 5:12 a.m.

29 +0

890 +2

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shapash by MAIF

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

updated at June 6, 2024, 1:47 p.m.

36 -1

2,670 +14

325 +1

xai by EthicalML

XAI - An eXplainability toolbox for machine learning

updated at June 3, 2024, 2:44 p.m.

44 +0

1,071 +1

160 +0