Question 1: Considering the following scenario:
I have a dataset where my treatment is given to 94% of the total base so the control is just 6%. Is it the right to approach to use this imbalanced data into the model with specifying the p=0.94 in the TransformedOutcome method?
Or if a sampling is needed, how to deal with the validation data? Should that also be sampled?
Question 2:
I am using the trained model on a hold out data and I have the uplift scores. But I am getting a huge chunk of customers getting exactly the same uplift score. Any thoughts on why this occurs?
Hi, I have two questions.
Question 1: Considering the following scenario: I have a dataset where my treatment is given to 94% of the total base so the control is just 6%. Is it the right to approach to use this imbalanced data into the model with specifying the p=0.94 in the TransformedOutcome method? Or if a sampling is needed, how to deal with the validation data? Should that also be sampled?
Question 2: I am using the trained model on a hold out data and I have the uplift scores. But I am getting a huge chunk of customers getting exactly the same uplift score. Any thoughts on why this occurs?
Please advice.