Is there a simple/built-in method of ensuring that if you extract 2+ subsets from the same dataset (using Genetic Feature Selection), that the features found in the first subset are not found in another subset? I.e., Obtain a series of series of subsets that are "symmetrically different" mathematically.
I'm wondering since I want to have each subset have it's own 'branch' before coming all together and the presence of duplicated features makes understanding the 'feature importance' more difficult. Just asking to ensure I'm not coding for something that exists but I couldn't find it.
Is there a simple/built-in method of ensuring that if you extract 2+ subsets from the same dataset (using Genetic Feature Selection), that the features found in the first subset are not found in another subset? I.e., Obtain a series of series of subsets that are "symmetrically different" mathematically.
I'm wondering since I want to have each subset have it's own 'branch' before coming all together and the presence of duplicated features makes understanding the 'feature importance' more difficult. Just asking to ensure I'm not coding for something that exists but I couldn't find it.