What is the connection between Random Forest and ensemble entropy minimization?

Random Forest reduces ensemble-level entropy through aggregation of multiple low-entropy partitions.

Each tree minimizes local entropy via greedy splitting. When aggregated, RF reduces uncertainty in class probability estimates across feature space. This ensemble entropy minimization leads to smoother probability surfaces and improved generalization.