[D] (Interview question) Comparing two models with and without negative sampling but same AUC and logloss on the test dataset: which model is better?

Hi, I've recently gotten this question at a tech company during a ML interview. Let's say we built a classifier that predicts users' certain actions (e.g., clicks on ads).

(1) How do we evaluate this model (assuming that it's a heavily imbalanced dataset)

\- I mentioned that we can use AUC and normalized cross entropy. (Definition: the average log loss per impression divided by what the average log loss per impression would be if a model predicted the background click …

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