Hi, I found a small mistake in one of the course videos (sorry if this is the wrong place to post such issues, I tried to leave feedback directly on pluralsight but couldn't figure out how to do so).
Specifically, in the video "Evaluating the Naive Bayes Model", at time 1:30, I believe the FP and FN labels are swapped. FP should be bottom left, FN should be top right. I noticed this when trying to compute the recall, which (if FN were equal to 33) would be TP / (TP + FN) = 52 / (52 + 33) = 0.61, not 0.65 which we should be getting.
I also recomputed the number of true/false positives and negatives from scratch using numpy primitives to verify this:
Hi, I found a small mistake in one of the course videos (sorry if this is the wrong place to post such issues, I tried to leave feedback directly on pluralsight but couldn't figure out how to do so).
Specifically, in the video "Evaluating the Naive Bayes Model", at time 1:30, I believe the FP and FN labels are swapped. FP should be bottom left, FN should be top right. I noticed this when trying to compute the recall, which (if FN were equal to 33) would be TP / (TP + FN) = 52 / (52 + 33) = 0.61, not 0.65 which we should be getting.
I also recomputed the number of true/false positives and negatives from scratch using numpy primitives to verify this:
Output: