Some questions about `prune_tree`.

The prune_tree function for classification trees internally calls _prune_run which computes the purity using the zero-one loss. However, decision trees are built using the entropy purity. I'm not sure if this is done on purpose or if it's a bug.

The latter can be fixed easily, but we might also address the more general problem and make prune_tree criterion-agnostic by storing the purity of the node in a struct field (which is already a byproduct of tree building) and, instead of recomputing the node purity, have the function refer to that field. This will also make the same prune_tree function work on both regression and classification trees.

Start by tracing prune_tree and its internal _prune_run call, then compare the purity computed during pruning with the entropy-based purity used when building classification trees. Review the existing discussion before deciding whether to correct the classification behavior or make pruning criterion-agnostic for both classification and regression trees.