Linked Questions
12 questions linked to/from How to derive the probabilistic interpretation of the AUC?
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Why is ROC AUC equivalent to the probability that two randomly-selected samples are correctly ranked? [duplicate]
I found there are two ways to understand what AUC stands for but I couldn't get why these two interpretations are equivalent mathematically.
In the first interpretation, AUC is the area under the ...
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"ROC AUC reflects the likelihood that a random positive instance will be located to the right of a random negative instance". How come? [duplicate]
According to this webpage,
ROC AUC reflects the likelihood that a random positive (red) instance will be located to the right of a random negative (gray) instance.
Would you please explain this ...
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292
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What does AUC stand for and what is it?
Searched high and low and have not been able to find out what AUC, as in related to prediction, stands for or means.
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Is AUC the probability of correctly classifying a randomly selected instance from each class?
I read this caption in a paper and have never seen AUC described in this way anywhere else. Is this true? Is there a proof or simple way to see this?
Fig. 2 shows the prediction accuracy of ...
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AUC for someone with no stats knowledge
Can someone explain what area under the curve means for someone with absolutely no stats knowledge? For example, if a model claims an AUC of 0.9, does that mean that it makes an accurate prediction 90%...
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How to report AUC from Cox Regression?
I need to calculate the AUC for a Cox regression model. SAS is giving me a time dependent AUC as below. How do I report this for the paper?
Thanks!!
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Why is $AUC=0.5$ and a 45-degree line for a ROC curve considered baseline performance?
$AUC=0.5$ and an ROC curve of a 45-degree line often are considered the baseline performance of a model, one that gets absolutely nothing from the features.
If we predict the same (prior) probability ...
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3
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Why do we look at multiple thresholds in AUC
For AUC ROC, why do we have a graph of multiple thresholds when in the end, we will only use one of those thresholds (so why not just choose the threshold and compare that one value across models)?
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Showing that $P(X_1>X_2) = \int_{0}^1 P(X_1>X_2 | X_2=x) f_{X_2}(x) dx$
I am going through this post in trying to prove the probabilistic interpretation of the AUC for a ROC Curve (for a classifier):
The AUC for a ROC curve is the the probability of the classifier ...
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3
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What is the relationship between the Brier score "refinement" and the area under the ROC curve?
In the Wikipedia article on Brier score, there is a claim that the "refinement" in the two-component decomposition of Brier score is related to the area under the receiver-operator ...
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How to derive the the AUROC from the Bayes Minimum Risk (Hand 2009)?
The area-under-the-receiver-operating-characteristic-curve (AUROC) can be derived from the Bayes Minimum Risk. The derivation requires the assumption that the exact costs are unknown but follow a ...
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Regarding area ABOVE the curve - complement of AUROC
When handling probabilities close to 1, it is often more helpful to use the complement (i.e. 1-P).
For instance, we say "there is a 1 in 1,000,000 chance of an event occurring", instead of &...
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