AI RESEARCH
From Decision Trees to Boolean Logic: A Fast and Unified SHAP Algorithm
arXiv CS.LG
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ArXi:2511.09376v2 Announce Type: replace SHapley Additive exPlanations (SHAP) is a key tool for interpreting decision tree ensembles by assigning contribution values to features. It is widely used in finance, advertising, medicine, and other domains. Two main approaches to SHAP calculation exist: Path-Dependent SHAP, which leverages the tree structure for efficiency, and Background SHAP, which uses a background dataset to estimate feature distributions.