COAT framework learns interpretable prescriptive policies from observational data using counterfactual estimates and mixed-integer optimization for constrained decision making
Read the original at arxiv.org→arXiv:2607.14318v1 Announce Type: new Abstract: We introduce COAT (Counterfactual Optimal Action Tree), a framework for learning interpretable prescriptive policies from observational data. COAT combines...
Original headline: "Counterfactual Optimal Action Trees (COAT): Interpretable Prescriptive Policies from Observational Data"