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?
Discussion 2
Follow the attached instructions to complete this work. Using ChatGPT or another generative AI tool, you will request SQL code for a business problem using simple user requirement terms. Then you will plug that into MySQL to reverse engineer an ERD. You and your classmates will discuss misalignments between what