Criteria used to create and select leaf nodes in sklearn
Pre-pruning is handled by a variety of parameters:
max_depth, min_samples_split, min_samples_leaf, min_weight_fraction_leaf, max_leaf_nodes, and min_impurity_decrease.
Post-pruning is relatively new to sklearn, and is accomplished with minimal cost-complexity pruning, parameter ccp_alpha.