NO.PZ2023040502000081
问题如下:
Exhibit 1 provides results from a sample of loans
from the ALPHA model that compared expected and actual defaults over the past
12 months.
While reviewing
the model documentation, Lovell confirms that the model was able to correctly
predict a default in 5,290 instances of the model prediction dataset after the
completed data wrangling.
Based on the
results provided for the ALPHA model (Exhibit 1) and its associated
documentation, the precision of the model is closest to:
选项:
A.
75.4%
B.
85.5%
C.
95.1%
解释:
C is correct.
Precision (P) = TP/(TP + FP), where
TP = True positive = 5,290
FP = False positive = Type 1 error = 273
FN = False negative = Type 2 error = 894
P = 5,290/(5,290 + 273) = 5,290/5,563 =
95.1%.
A is incorrect.
The calculation incorrectly uses the total number of predictions in the denominator:
5,290/7,018 = 75.4%.
B is incorrect.
The calculation uses the correct equation but incorrectly treats a Type 2 error
as a false positive and a Type 1 error as a false negative:
P = TP/(TP + FP) = 5,290/(5,290 + 894) =
5,290/6,184 = 85.5%.
请问 correctly predict 不包括FN吗 why