In another post, we discussed the use of ROC curves to describe the goodness of a classifier. I did say that I would post a brief paragraph on the interpretation of the diagonal. If you look around, some say that it describes the "strategy of randomly guessing a class", that it is obtained with "a diagnostic test that is no better than chance level," even obtained by "making a prediction by tossing of an unbiased coin."
Let us get back to ROC curves to illustrate those points. Consider a very simple dataset with 10 observations (that is not linearly separable):
