Policy using Treatment Classes with DynamicDML
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Description
@kbattocchi Hi Keith!
I was curious to learn if the DynamicDML class is able to use Treatment Classes (like the DRPolicyForest) instead of discrete/continous variables? I am looking to understand what the optimal NEXT treatment in sequence for a given user would be? My treatment classes look like this:
Treatment A : consists of a distribution of possible values
Treatment B : consists of a distribution of possible values
Example Policy: User X received Treatment B on day 1 and Treatment A on day 2. What is the next best Treatment for the next time?
Is this something the DynamicDML can assist with (or any alternative)?
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Research direction
The question centers on DynamicDML and compares it with DRPolicyForest; start by reviewing those entry points and their treatment representations. Determine whether sequential treatment classes are supported, and document the applicable alternative or the scope needed to support the requested next-treatment policy.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100