# how to evaluate logistic regression given binary labels [duplicate]

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