18.7 In the recursive construction of decision trees, it sometimes occurs that a mixed set of positive and negative examples remains at a leaf node, even after all the attributes have been used.

Suppose that we have/) positive examples and n negative examples.

a. Show that the solution used by DECISION-TREE-LEARNING, which picks the majority classification, minimizes the absolute error over the set of examples at the leaf.

CLASS PROBABILITY

b. Show that returning the class probability pl(p + n) minimizes the sum of squared errors.