print.multi_causal_forest

<p>Additional arguments (currently ignored).</p>

<p>Print a multi_causal_forest object.</p>

Learn optimal policies via doubly robust empirical
welfare maximization over trees. This package implements the multi-action doubly
robust approach of Zhou, Athey and Wager (2018) <arXiv:1810.04778> in the case where
we want to learn policies that belong to the class of depth k decision trees.

Erik Sverdrup

policytree

Policy Learning via Doubly Robust Empirical Welfare Maximization
over Trees

print.multi_causal_forest: Print a multi_causal_forest object.

Description

Usage

Arguments