How does Random Forest relate to decision boundary curvature approximation?

Random Forest approximates curved boundaries via piecewise axis-aligned segmentation.

Although individual trees cannot create curved splits, dense ensembles of axis-aligned partitions approximate curvature through fine-grained step approximations. This is analogous to Riemann sums approximating integrals, where increasing tree density improves boundary resolution.