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In dataset D2, the proportion of fraud cases is 0.01%. Which of the following statements are true? Choose all that apply. A. A trivial model can yield classification accuracy of 99.99%. B. The worst-case area under the ROC curve is 50%. C. The confusion matrix is a better metric than the classification accuracy. D. I can compute the area under the ROC curve from the confusion matrix if I obtain the confusion matrix at multiple values of the decision threshold.

In dataset D2, the proportion of fraud cases is 0.01%. Which of the following statements are true? Choose all that apply. A. A trivial model can yield classification accuracy of 99.99%. B. The worst-case area under the ROC curve is 50%. C. The confusion matrix is a better metric than the classification accuracy. D. I can compute the area under the ROC curve from the confusion matrix if I obtain the confusion matrix at multiple values of the decision threshold.

Computer Networking: A Top-Down Approach (7th Edition)
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
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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In dataset D2, the proportion of fraud cases is 0.01%. Which of the following statements are true? Choose all that apply. A. A trivial model can yield classification accuracy of 99.99%. B. The worst-case area under the ROC curve is 50%. C. The confusion matrix is a better metric than the classification accuracy. D. I can compute the area under the ROC curve from the confusion matrix if I obtain the confusion matrix at multiple values of the decision threshold.
Transcribed Image Text:In dataset D2, the proportion of fraud cases is 0.01%. Which of the following statements are true? Choose all that apply. A. A trivial model can yield classification accuracy of 99.99%. B. The worst-case area under the ROC curve is 50%. C. The confusion matrix is a better metric than the classification accuracy. D. I can compute the area under the ROC curve from the confusion matrix if I obtain the confusion matrix at multiple values of the decision threshold.
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