Figure 1 shows the general discriminatory test for health status prediction."Perfect testcut-offTrue negative; TN(specificity)True positive; TP(sensitivity)False negative (FN)False positive (FP)HealthySick(a)Testcut-offMoving cut-off to leftreduces false negatives(higher specificity)at cost ofreduced sensitivityMoving cut-off to rightreduces false positives(higher sensitivity)at cost ofreduced specificityTNTPFNFPHealthySick(b)Figure 1. The Discriminatory Test with (a) A Good Discrimination Test Cut-off,and (b) A Bad Discrimination Test Cut-offi. What is your next action, if you obtain a perfect discriminatory test result(where both false negative and false positive rate are near zero) during modeltraining? Justify your action.ii. In which phase of machine learning methodology do you move the test cut-offpoint as shown in Figure 1(b)? Justify why you should do that.

Hypothesis testing is a vital process in inferential statistics where the goal is to use sample data…

Answered: i. What is your next action, if you…

Principles Of Marketing

17th Edition

ISBN:9780134492513

Author:Kotler, Philip, Armstrong, Gary (gary M.)

Publisher:Kotler, Philip, Armstrong, Gary (gary M.)

Chapter1: Marketing: Creating Customer Value And Engagement

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i. What is your next action, if you obtain a perfect discriminatory test result (where both false negative and false positive rate are near zero) during model training? Justify your action.