3 papers
cs.LG2026
Woodelf++: A Fast and Unified Partial Dependence Plot Algorithm for Decision Tree Ensembles
Ron Wettenstein, Alexander Nadel, Udi Boker
Partial Dependence Plots (PDPs) visualize how changes in a single feature affect the average model prediction. They are widely used in practice to interpret decision tree ensembles…
cs.LG2026
WOODELF-HD: Efficient Background SHAP for High-Depth Decision Trees
Ron Wettenstein, Alexander Nadel, Udi Boker
Decision-tree ensembles are a cornerstone of predictive modeling, and SHAP is a standard framework for interpreting their predictions. Among its variants, Background SHAP offers hi…
cs.LG2026
From Decision Trees to Boolean Logic: A Fast and Unified SHAP Algorithm
Alexander Nadel, Ron Wettenstein
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,…