SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using classic Shapley values from game theory and their related extensions.
AI named SHAP Documentation from October 2025 to September 2026.
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