Nathanael Jo – Optimization Online

ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription

Published: 2023/07/31, Updated: 2026/08/14

ODTlearn is an open source Python package that provides methods for learning optimal decision trees for high-stakes predictive and prescriptive tasks based on the state-of-the-art mixed-integer optimization (MIO) framework proposed Aghaei et al. (2025). The current version of the package provides implementations for learning optimal classification trees, optimal fair classification trees, optimal prescriptive trees from … Read more

Learning Optimal Prescriptive Trees from Observational Data

Published: 2021/08/26, Updated: 2023/09/22

(Mixed) Integer Linear Programming, Applications - OR and Management Sciences causal inference, interpretability, mixed-integer programming, observational data, prescriptive trees

We consider the problem of learning an optimal prescriptive tree (i.e., an interpretable treatment assignment policy in the form of a binary tree) of moderate depth, from observational data. This problem arises in numerous socially important domains such as public health and personalized medicine, where interpretable and data-driven interventions are sought based on data gathered … Read more