What is the role of entropy plateauing in stopping tree growth?

Entropy plateauing indicates diminishing returns from further splits, signaling optimal stopping.

As a decision tree grows, early splits significantly reduce entropy by separating dominant patterns. However, after a certain depth, additional splits yield minimal entropy reduction because remaining subsets are already relatively pure or noisy. This flattening of entropy gain is called plateauing. It is a strong signal for stopping or pruning because further splits mostly capture noise. Many pruning strategies implicitly rely on this behavior by penalizing small impurity gains.