Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees
Example data generating process from Offline Multi-Action Policy Learn...
Estimate mean rewards for each treatment
Writes each node information If it is a leaf node: show it in differen...
Matrix of scores for each treatment
Export a tree in DOT format. This function generates a GraphViz repres...
Example data generating process from Policy Learning With Observationa...
Hybrid tree search
A utility function for generating random trees for test purposes.
(deprecated) One vs. all causal forest for multiple treatment effect e...
Plot a policy_tree tree object.
Fit a policy with exact tree search
policytree: Policy Learning via Doubly Robust Empirical Welfare Maximi...
Predict method for policy_tree
Predict with the above test tree.
Print a policy_tree object.
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.