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On the test set of a binary classification problem, the p25, p50 and p75 of the predictions are very close to each other (e.g. 0.123).

Is it possible that my model can achieve a high AUC-ROC (e.g. 0.85) despite giving the same probability prediction for almost the rows?

The data is imbalanced.

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  • $\begingroup$ If it is a imbalanced class it can happen $\endgroup$
    – Ashwiniku918
    Commented Apr 6, 2022 at 18:37
  • $\begingroup$ "very close to each other", or "same for nearly all rows"? Some more details on the distribution of predicted probabilities, please. Also, what kind of model? $\endgroup$
    – Ben Reiniger ♦
    Commented Apr 7, 2022 at 0:01
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    $\begingroup$ ROC only cares about ranking. So 0.1231 and 0.1232 are as far apart as -100 and +1000: 1 rank. Can you show the actual values? $\endgroup$
    – Calimo
    Commented Apr 7, 2022 at 5:38

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