hi olivier,
just a question on this statement:
Random Forest (and decision tree-based models in general) are scale
> independent.
>
in many cases with fat data (small samples<50 x many features>100000) i
have found that standardizing helps quite a bit in case of extra trees. i
still don't have a good understanding as to why this is the case. it could
simply be small sample bias that i am seeing. but extra trees are also
supposed to be resilient to overfitting.
any thoughts?
cheers,
satra
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