How do Decision Trees handle feature scaling and normalization?

Decision Trees do not require feature scaling because they split based on thresholds, not distance metrics.

Unlike models such as SVM or KNN, Decision Trees evaluate conditions like feature <= threshold. Since ordering of values matters, not magnitude, scaling does not affect splits. However, extreme distributions or noisy features may still impact threshold selection indirectly.