extend code to feature groups

[shaayaansayed]

correct me if I'm wrong, but I don't believe the current code is setup to calculate values for feature groups.

Can you confirm I'm understanding this correctly? To extend the code for groups, we would want to select subsets over feature groups rather than individual features. Then when measuring predictiveness, we include all features that are part of the selected feature groups. So for example, if we have groups:

vitals = [blood_pressure, heart_rate] labs = [sodium, potassium, sugar] diagnoses = [kidney, heart, liver]

If S = [0, 1], then we train a model with blood_pressure, heart rate, sodium, potassium, and sugar.

Would we need to normalize anything?