1 Consider an ensemble learning algorithm that uses simple majority voting among K learned hypotheses. Suppose that each hypothesis has error  and that the errors made by each hypothesis are independent of the others’. Calculate a formula for the error of the ensemble algorithm in terms of K and , and evaluate it for the cases where K =5, 10, and 20 and =0.1, 0.2, and 0.4. If the independence assumption is removed, is it possible for the ensemble error to be worse than ?