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SESK: Stuff Everyone Should Know · sesk.info/ai-auc-random-half

What AUC (area under the ROC curve) does a model that just guesses randomly get?

0.5. A perfect model gets 1.0.

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  1. 0
  2. 0.5 ✔
  3. 1.0

Why: AUC is the chance the model ranks a random positive above a random negative. Random guessing gets that right half the time, so 0.5. A perfect ranker scores 1.0.

Huh, didn't know that: The ROC curve plots true positive rate against false positive rate at every threshold.

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My coin flip model has an AUC of 0.5. It is confident, just not helpful.
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References

Answer: 0.5. AUC is the chance the model ranks a random positive above a random negative. Random guessing gets that right half the time, so 0.5. A perfect ranker scores 1.0.

  1. Google ML Crash Course: ROC and AUC developers.google.com/machine-learning/crash-course/classification/roc-and-auc
    The AUC is 0.5, representing a 50% probability of correctly ranking a random positive and negative example.
    Checked 2026-10-10.

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