Different result with roc_auc_score() and auc()

Question

I have trouble understanding the difference (if there is one) between roc_auc_score() and auc() in scikit-learn.

Im tying to predict a bina

Answer 1

predict returns only one class or the other. Then you compute a ROC with the results of predict on a classifier, there are only three thresholds (trial all one class, trivial all the other class, and in between). Your ROC curve looks like this:

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Meanwhile, predict_proba() returns an entire range of probabilities, so now you can put more than three thresholds on your data.

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Hence different areas.