Solved – Determine how good an AUC is (Area under the Curve of ROC)

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I'm currently working on a project involving using different sets of data as a predictor to predict the outcome of out-sample data. I use AUC (Area under the Curve of ROC) to compare the performances of each set of data.

I am familiar with the theory behind AUC and ROC, but I'm wondering is there a precise standard for assessing AUC, for example, if an AUC outcome is over 0.75, it will be classified as a 'GOOD AUC', or below 0.55, it will be classified as a 'BAD AUC'.

Is there such a standard, or AUC is always for comparing only?

Best Answer

From the comments:

Calimo: If you are a trader and you can get an AUC of 0.501 in predicting future financial transactions, you're the richest man in the world. If you are a CPU engineer and your design gets an AUC of 0.999 at telling if a bit is 0 or 1, you have a useless piece of silicon.

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