We use AdaBoost to perform classification on 5 objects

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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We use AdaBoost to perform classification on 5 objects
(1) If first classifier f, classifies 2 objects incorrectly (classification error = 0.4). What
weight should be assigned to objects that were classified correctly and incorrectly,
respectively, such that, under the new weights, the performance of fi would be the
same as random (classification error = 0.5).
(2) Next, choose a second classifier f2, what is the classification error? What is the new
weight?
(3) Find a third classifier f3, what is the classification error? What is the new weight?
(4) Combine the three classifiers using AdaBoost. What is the final classifier H(x)? What is
the final error rate?
Transcribed Image Text:We use AdaBoost to perform classification on 5 objects (1) If first classifier f, classifies 2 objects incorrectly (classification error = 0.4). What weight should be assigned to objects that were classified correctly and incorrectly, respectively, such that, under the new weights, the performance of fi would be the same as random (classification error = 0.5). (2) Next, choose a second classifier f2, what is the classification error? What is the new weight? (3) Find a third classifier f3, what is the classification error? What is the new weight? (4) Combine the three classifiers using AdaBoost. What is the final classifier H(x)? What is the final error rate?
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