policytree | Policy learning via doubly robust empirical welfare | Machine Learning library

policytree is a R library typically used in Artificial Intelligence, Machine Learning, Pytorch applications. policytree has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

A package for learning optimal policies via doubly robust empirical welfare maximization over trees. Many practical policy applications require interpretable predictions. For example, a drug prescription guide that follows a simple 2-question Yes/No checklist can be encoded as a depth 2 decision tree (does the patient have a heart condition - etc.). This package implements the multi-action doubly robust approach of Zhou et al. (2018) in the case where we want to learn policies that belong to the class of depth k decision trees.