Let me explain what I mean by unfairness.
Let's say I have a multi-class classification problem where I am trying to predict the 'best drug' (among multiple candidate drugs) for each patient. So for each entry (patient) in my database, I have recorded my target variable which is the 'best drug'.
The problem is that each patient didn't try all the candidate drugs but only a smaller set of them (set that I didn't record). The only thing I know is the 'best' one among this smaller set, and what I would like to predict is the best one among all the possible drugs.
I wanted if you knew any techniques or models that can handle this type of 'unfairness'?