Someone from SAS may be able to provide a more accurate respose, but, as far as I know, the algorithm behind the Interactive Grouping Node uses a two-step approach for interval variables:
1. First, it "discretizes" the variables by creating groups, essentially transforming the variables from interval to nominal
2. Secondly, applies a Tree-based logic to find the optimal binning based on the groups from step (1)
My understanding is the above approach is used only for computational efficiency reasons, because, in general, interval variables may have hundreds, if not, thousands of different values whihc would make it too computational intensive for a Tree algorithm to fully evaluate.
Therefore, by carrying out a pre-binning step, you end up with far fewer categories which then can be optimised based on a Tree-like algorithm.
Lastly, from my experience, unless you have a good reason for using "bucket", my advice is to always go for "quantile" (i.e. that should be the default approach unless, for some specific reason, you want to have groups defined by having the same width).
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