Does anybody what are the implications of having overlaps in between different set of interactions. For example, an interaction constraint of the form:
[[0, 1, 2, 3], [1, 2, 3, 4], [2, 3, 4, 5]]
I want to do this because for my data neighbouring features are highly correlated. My thinking is that by doing this I can manage to limit model complexity by eliminating first order interactions in between distant features. But I don’t really now the actual implications for the algorithm of defining that kind of interaction. Will it simply be reduced to [0,1,2,3,4,5], and therefore achieve nothing?