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cs.LG2026

Counterfactual Optimal Action Trees (COAT): Interpretable Prescriptive Policies from Observational Data

Youssef Drissi, Markus Ettl, Shivaram Subramanian +2

The paper presents COAT, a method that builds interpretable decision trees for prescribing actions by combining counterfactual outcome estimates with mixed‑integer optimization, an…