Common misconceptions and pitfalls of using ROC
Receiver operating curve (ROC) An ROC curve is a commonly used technique to visualise, organise, and select or compare classifiers based on their performance. Where a classifier is usually binary with two possible outcomes. Historically, the use of ROCs comes from WW-II where it was used for assessing performance of signal detection and specifically to find out whether a signal from radar was a true positive or a false positive. The guy who operated the radar receiver would be known as ‘receiver operator’, and hence, ROC got its name :) Sometime in the 1970s ROC started making its appearance in the field of medicine, where it was used to evaluate and compare algorithms. Now, I will elaborate on understanding different components of an ROC, what they mean, and how they are used. Let's take an example where an observed instance is mapped to one of two class labels, say COVID positive or negative. This test can be performed based on a variety of factors a.k.a features. A...