I've encountered an interview question:
Given several binary labels, each label represents a user will click a certain advertisement or not, we have a trained logistic model and its predicted probability of a user clicking the advertisement. How to evaluate this trained logistic model?
I answered by using different thresholds on the predicted probability, we can easily plot the ROC curve and then area under the curve should be a measure. The interviewer said that this is Okay, but can you give me other methods? I'm wondering how to answer this question. By the way, I failed at last.
click or not predicted user1 1 0.8 user2 1 0.6 user3 0 0.4 ... ... ... usern 0 0.3