what happens to the sample points on pruned leaves I think I understand what pruning is (in concept) in a decision tree. What is not so clear to me (in reading) is what happens to the pruned observations. What do you do with them? Are they just simply not used and forgotten?
What bothers me is the &quot;hole&quot; left behind by the pruned node. What if a future $Y$ needs to be predicted at that node? Do you go to the parent node and treat that parent node as an end node and predict $Y$ by the data at that parent node (even though some data at the parent node continue to be divided in sub-nodes, other than the pruned node)?
Once you prune nodes, they get removed from the tree altogether, so you wouldn't be able to predict based on them.
Typically, hyperparaneter tuning is used to ensure that the right nodes are pruned. Obviously, there is always a trade-off.