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?
D 8 of 485
Follow the attached instructions to complete this work. Strategies for Addressing Global Threats You will start by writing a short paper as described in the discussion question. You will be using information from this week’s readings and from your own research to address the information needs expressed in the