How does Random Forest behave under multi-resolution feature scales?

RF naturally handles multi-scale feature interactions due to hierarchical splits.

Decision trees partition feature space recursively, effectively capturing coarse-to-fine structures. Random Forest aggregates these multi-resolution representations, allowing it to model both global trends and local variations simultaneously without explicit feature scaling transformations.