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6) We have a logistic regression model that computes the probability p(x) that a given input a belongs to the positive class. For a threshold 0 = (0, 1), the class labels f(x) = {negative, positive} are predicted as given below. f(x)= negative, positive, if p(x) < 0 if p(2) ≥0 For 0 = 0.5, we have TPR = 0.8 and FPR = 0.3. Then which of the following statement(s) is/are correct? For = 0.4, the FPR could be lower than 0.25. For = 0.4, the FPR could be higher than 0.45. For = 0.6, the TPR must be higher than 0.85. For = 0.6, the TPR could be higher than 0.85. For = 0.4, the TPR must be lower than 0.75. For = 0.4, the TPR could be lower than 0.75.

6) We have a logistic regression model that computes the probability p(x) that a given input a belongs to the positive class. For a threshold 0 = (0, 1), the class labels f(x) = {negative, positive} are predicted as given below. f(x)= negative, positive, if p(x) < 0 if p(2) ≥0 For 0 = 0.5, we have TPR = 0.8 and FPR = 0.3. Then which of the following statement(s) is/are correct? For = 0.4, the FPR could be lower than 0.25. For = 0.4, the FPR could be higher than 0.45. For = 0.6, the TPR must be higher than 0.85. For = 0.6, the TPR could be higher than 0.85. For = 0.4, the TPR must be lower than 0.75. For = 0.4, the TPR could be lower than 0.75.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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6) We have a logistic regression model that computes the probability p(x) that a given input a belongs to the positive class. For a threshold 0 = (0, 1), the class labels f(x) = {negative, positive} are predicted as given below. f(x)= negative, positive, if p(x) < 0 if p(2) ≥0 For 0 = 0.5, we have TPR = 0.8 and FPR = 0.3. Then which of the following statement(s) is/are correct? For = 0.4, the FPR could be lower than 0.25. For = 0.4, the FPR could be higher than 0.45. For = 0.6, the TPR must be higher than 0.85. For = 0.6, the TPR could be higher than 0.85. For = 0.4, the TPR must be lower than 0.75. For = 0.4, the TPR could be lower than 0.75.
Transcribed Image Text:6) We have a logistic regression model that computes the probability p(x) that a given input a belongs to the positive class. For a threshold 0 = (0, 1), the class labels f(x) = {negative, positive} are predicted as given below. f(x)= negative, positive, if p(x) < 0 if p(2) ≥0 For 0 = 0.5, we have TPR = 0.8 and FPR = 0.3. Then which of the following statement(s) is/are correct? For = 0.4, the FPR could be lower than 0.25. For = 0.4, the FPR could be higher than 0.45. For = 0.6, the TPR must be higher than 0.85. For = 0.6, the TPR could be higher than 0.85. For = 0.4, the TPR must be lower than 0.75. For = 0.4, the TPR could be lower than 0.75.
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