Refer to the exhibit.
You have scored your Naive bayesian classifier model on a hold out test data for cross validation and determined the way the samples scored and tabulated them as shown in the exhibit.
What are the the False Positive Rate (FPR) and the False Negative Rate (FNR) of the model?
A.
FPR = 15/262
FNR = 26/288
B.
FPR = 26/288
FNR = 15/262
C.
FPR = 262/15
FNR = 288/26
D.
FPR = 288/26
FNR = 262/15
None of the Answers are correct. It can be (A) provided, FPR = 15/362 (instead of 262 in the denominator) and FNR = 26/288.
FPR = 15 / (347 + 15) = 15/363.
Anybody in this comment section, please do correct me if I am wrong.
0
0
FPR = 15 / (347 + 15) = 15/363
FNR = 26 / (262 + 26) = 26/288
0
0
Dippies, as you asked, you are wrong.
FPR = 15/362
FNR = 26/288
0
1
He’s not wrong you dumbsh*t.
FPR = FP/(FP+TN)
FNR = FN/(FN+TP)
0
0
FPR = FP/Actual NO = 15/362
FNR = FN/Actual YES = 26/288
Answer A has a typo – it should be 362 instead of 262. Which dumbsh** wrote this question?
2
0