ROOT: Rashomon Set of Optimal Trees

2026 Dataset Open access

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Authors: Yiren Hou, Peter Liu, Sean McGrath, Harsh Parikh
DOI: 10.32614/cran.package.root
Cited by: 0
References: 1

Abstract

Implements a general framework for globally optimizing user-specified objective functionals over interpretable binary weight functions represented as sparse decision trees, called ROOT (Rashomon Set of Optimal Trees). It searches over candidate trees to construct a Rashomon set of near-optimal solutions and derives a summary tree highlighting stable patterns in the optimized weights. ROOT includes a built-in generalizability mode for identifying subgroups in trial settings for transportability analyses (Parikh et al. (2025) ).

Fields of Study & Subjects

Advanced Causal Inference Techniques Data Mining Algorithms and Applications Explainable Artificial Intelligence (XAI)

Publication details

Publication date
10 March 2026
Language
EN
Document type
Dataset