Refer to the exhibit:

An analyst examined logistic regression models for predicting whether a customer would make a purchase. The ROC curve displayed summarizes the models. Using the selected model and the analyst's decision rule, 25% of the customers who did not make a purchase are incorrectly classified as purchasers.
What can be concluded from the graph?
Suggested Answer: C
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14 comments · newest first
SU
Sueann
12 months ago
I thought it would be lower than 50%, interesting!
VI
Vincent
12 months ago
Definitely not 95%, that seems too high.
IR
Irma
1 year ago
I'm guessing it's closer to 85% accuracy based on the ROC curve.
ME
Melissia
1 year ago
Wait, how can we be sure about the correct classifications?
LU
Luisa
1 year ago
Looks like 25% false positives is pretty rough.
JO
Johnson
1 year ago
I feel like the correct answer is probably C or D, but I need to think about how the misclassification affects the true positive rate.
KA
Katlyn
1 year ago
If 25% of non-purchasers are misclassified, that might suggest a higher true positive rate, but I can't recall the exact numbers for correct classifications.
VE
Veta
1 year ago
I think I saw a similar question where we had to interpret the ROC curve, and it was about the true positive rate being higher than the false positive rate.
DE
Denae
1 year ago
I remember something about ROC curves indicating true positive rates, but I'm not sure how that relates to the percentages given here.
BR
Brandee
1 year ago
Hmm, I'm a little unsure about this one. I know manual lenses have good iris control, but I'm not sure if they're the best in all lighting conditions. I might need to think this through a bit more.
MA
Marsha
1 year ago
Opening up the RDS instances to all IP addresses? That sounds like a huge security risk. I'll steer clear of that.
FA
Fannie
1 year ago
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DU
Dulce
1 year ago
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CH
Cherry
1 year ago
I remember studying the different solutions, but I'm not sure if FlexStack is part of Cisco's offerings.