A confusion matrix compares the predictions to the true default statuses for the 10, 000 observations in the Default dat
Posted: Mon Jun 06, 2022 6:21 am
A confusion matrix compares the predictions to the true default
statuses for the 10, 000 observations in the Default data set.
Which statement is NOT correct? Hint: first reorganize the values
to the format seen in class.
Question 10 options:
The specificity (the percentage of non-defaulters that are
correctly identified) is 99.8% .
The sensitivity (the percentage of true defaulters that are
identified) is 77.9%.
The accuracy of the classifer is 97.25%.
From the perspective of a credit card company that is trying to
identify high-risk individuals, an error rate of 75.7% among
individuals who default may well be unacceptable.
statuses for the 10, 000 observations in the Default data set.
Which statement is NOT correct? Hint: first reorganize the values
to the format seen in class.
Question 10 options:
The specificity (the percentage of non-defaulters that are
correctly identified) is 99.8% .
The sensitivity (the percentage of true defaulters that are
identified) is 77.9%.
The accuracy of the classifer is 97.25%.
From the perspective of a credit card company that is trying to
identify high-risk individuals, an error rate of 75.7% among
individuals who default may well be unacceptable.