Suppose that we generate a training set from a decision tree and then apply decision-tree learning to that training tree. Is it the case that the learning algorithm will eventually return the correct...

Suppose that we generate a training set from a decision tree and then apply decision-tree learning to that training tree. Is it the case that the learning algorithm will eventually return the correct tree as the training-set size goes to infinity? Why or Why not?