SHAP (SHapley Additive exPlanations) values are a method used in machine learning to explain the output of complex models. They are based on Shapley values from cooperative game theory, which fairly distribute the "payout" among players based on their contribution to the total "game." In the context of catalysis, SHAP values can be used to interpret and understand the influence of different features or variables on the catalytic process.
