policytree
Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees
Learn optimal policies via doubly robust empirical welfare maximization over trees. Given doubly robust reward estimates, this package finds a rule-based treatment prescription policy, where the policy takes the form of a shallow decision tree that is globally (or close to) optimal.
- Version1.2.3
- R version≥ 3.5.0
- LicenseMIT
- LicenseLICENSE
- Needs compilation?Yes
- Last release06/13/2024
Team
Erik Sverdrup
Stefan Wager
Show author detailsRolesAuthorSusan Athey
Show author detailsRolesAuthorAyush Kanodia
Show author detailsRolesAuthorZhengyuan Zhou
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 549 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 21 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 7,722 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Jun 16, 2024 with 78 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports2 packages
- Suggests2 packages
- Linking To2 packages
- Reverse Imports2 packages