hostilereplicator t1_it85f0v wrote on October 21, 2022 at 5:01 PM

Reply to comment by robbsc in [D] Accurate blogs on machine learning? by likeamanyfacedgod

If you use precision, you also implicitly assume the data you're measuring on has the same positive:negative ratio as data you expect to see in the future (assuming you're going to deploy your model, rather than just doing retrospective analysis). FPR and TPR don't have this issue, so you can construct a test dataset with sufficiently large numbers of bot positives and negatives to get reliable measurements without worrying about the class imbalance.

robbsc t1_it87etm wrote on October 21, 2022 at 5:15 PM

Good point. The only valid criticism of roc curves that i can think of is that you can't always visually compare 2 full ROC curves without "zooming in" to the part you care about.