I have data where the objective is to use supervised learning to predict 4 different outcomes.
Say the classes are 1, 2, 3, 4. Though discrete, they are also hierarchical, where class 2 is of an extreme 'nature' than say class 1.
My question is how do I redefine the label column in such a way that it incorporates the hierarchical/weighting nature of the label classes?
I tried to redefine the label space into a (0,1) space where I can the map the classes to 1, 0.3,0.67 and 1 in in the space. This way, the problem becomes a regression problem. Is this a feasible route?
Another route is to fashion it as a straight multi-label problem but this does not reflect the hierarchical nature of the label.
I've had a look at How to conduct a multilevel model/regression for panel data in Python? but not much headway.
Suggestions on how to address the problem are welcome.