2.10 Consistent hypotheses. In this chapter, we showed that for a nite hypothesis set H, a consistent learning algorithm A is a PAC-learning algorithm. Here, we consider a converse question. Let Z be a nite set of m labeled points. Suppose that you are given a PAC-learning algorithm A. Show that you can use A and a nite training sample S to nd in polynomial time a hypothesis h 2 H that is consistent with Z, with high probability. (Hint: you can select an appropriate distribution D over Z and give a condition on R(h) for h to be consistent.)