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?
Wk4_300
Need help with a question. Due 3/10/2025 @ 9PM n the Week 4 labs, you performed tasks such as creating a cluster, restoring files, configuring account lockout policies, and verifying RAM usage. Note: Ensure you have completed all lab exercises from Week 4 before completing this assessment. Assessment Details Write a 350-