I have a model that produces a high ROC AUC (0.90), but at the same time a low average precision (0.30). From what I've found, I think it might have to do something with imbalanced data (which the dataset is). However, I cannot see how this imbalance results in this significant difference. Reading Davis' paper has not gotten me to an answer either.
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$\begingroup$ It's a bit hard to compare a global measure like ROC with one at a single threshold like precision. Have you considered you're not using an optimal threshold? $\endgroup$ – Calimo Jul 6 '18 at 5:55
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$\begingroup$ With average precision I mean the area under the Precision-Recall curve. $\endgroup$ – Icyeval Jul 6 '18 at 7:06
