What is ensemble pruning using greedy selection?

Greedy pruning selects models iteratively based on incremental performance gain.

Greedy ensemble pruning starts with an empty set and iteratively adds the model that maximally improves validation performance. This continues until no further improvement is observed. It reduces ensemble size while maintaining or improving accuracy. It is computationally efficient compared to exhaustive search but may not find global optimum.