RewardEstimation provides functionality for estimating rewards for use in evaluating prescriptive problems. This documentation includes:
- an overview of reward estimation, including an introduction to observational data and the difficulty of evaluating prescriptive problems, how reward estimation can assist with this task, and some best practices for practical application of reward estimation.
- guides to the reward estimation process and the relevant learners for each type of reward estimation:
- the RewardEstimation API reference
For more information and a demonstration of reward estimation applied to real problems, you can also refer to the following examples: