EconPapers    
Economics at your fingertips  
 

Fast Learning of Optimal Policy Trees

James Cussens, Julia Hatamyar, Vishalie Shah and Noemi Kreif

Papers from arXiv.org

Abstract: We develop and implement a version of the popular "policytree" method (Athey and Wager, 2021) using discrete optimisation techniques. We test the performance of our algorithm in finite samples and find an improvement in the runtime of optimal policy tree learning by a factor of nearly 50 compared to the original version. We provide an R package, "fastpolicytree", for public use.

Date: 2025-06
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2506.15435 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2506.15435

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().

 
Page updated 2025-06-19
Handle: RePEc:arx:papers:2506.15435