# Scaling dataset in Random Forest

Scaling a dataset for Random Forest modelling is not necessary. However, if we have already done the scaling and normalization to the dataset, will it impact our Random Forest modelling?

• It shouldn't matter. Also decision trees/RF should be invariant to scaling and normalization since they find partitions, which only depends on orderings.
– user327671
Aug 8 at 17:52
• Aug 10 at 18:31

• (+1) It's just the splitting point may change after the transformation, e.g. if we split the feature $x$ between $[1, 2]$, the split point will be $1.5$. But, if we split $x^2$ between $[1^2,2^2]$, then the split point will be $x^2=5/2\rightarrow x=\sqrt{5/2}$. This won't affect model build and training performance, but might have little effects on the test set. Aug 8 at 19:18