Question: 1 . Consider a binary classification problem with an ensemble learning algorithm that uses simple majority voting among K - learned hypotheses. Suppose that each

1 .

Consider a binary classification problem with an ensemble learning algorithm that uses simple majority voting among K

-

learned hypotheses. Suppose that each hypothesis has error E 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 E and evaluate it for the cases where K

= 5, 11,

and

21

and E

= 0.1, 0.2,

and

0.4 .

If the independence assumption is removed, is it possible for the ensemble error to be worse than E

?

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