Using Shapley Values

OLS coefficients give one fixed slope per feature, saying “everywhere in the data, a one‐unit change in xj​ shifts the prediction by βj​.” SHAP values, by contrast, come from a complex (e.g., tree‐based) model and tell you, for each individual case, exactly how much feature j moved that prediction above or below the model’s baseline. In short, OLS is a single global effect per feature, while SHAP breaks down each prediction into per‐feature contributions that can vary across observations.