3. Consider the decision tree shown in Figure 2a, and the corresponding training and test sets shown in the table below. The decision tree in Figure 2b is a pruned version of the original decision tree. B B 1 1 Figure 2a Figure 2b Training set Test set A B # of (+) instances # of (-) instances # of (+) instances # of (-) instances 5 3 4. 1 1 3 3 1 22 7 6. 3 1 32 3 15 5 5 2 2. 4. 5 d. What is the issue that you can identify in the decision tree of Figure 2a but not in the tree of Figure 2b? Explain how the pessimistic estimate of the classification error tries to capture that. 2. 1.

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