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?
SCMT699
please read attachments for assignment Feedback from week 10 Please address your design before your next submission. Its how you are going to go about conducting your research so other can duplicate it. This is a good book on it. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed