Interval-valued SHAP in Tree-Based Models
The method introduces interval-valued Shapley values to measure how robust feature importance is in tree models by simulating uncertainty through virtual samples added to leaf nodes. This allows researchers to quantify model stability and better identify uninformative features, offering a tractable way to assess interpretability in safety-critical systems.