Difference between revisions of "Area Under the ROC Curve"
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Zeno Gantner (talk | contribs) (AUC explained) |
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== External links == | == External links == | ||
* [[Wikipedia: Receiver operating characteristic]] | * [[Wikipedia: Receiver operating characteristic]] | ||
| − | * [http://github.com/zenogantner/MyMediaLite/blob/master/src/MyMediaLite/Eval/ | + | * [http://github.com/zenogantner/MyMediaLite/blob/master/src/MyMediaLite/Eval/Items.cs C# implementation of AUC evaluation] for binary responses (part of the [[MyMediaLite]] library) |
[[Category:Evaluation measure]] | [[Category:Evaluation measure]] | ||
Revision as of 11:04, 10 August 2011
The area under the ROC curve (AUC) is a measure for ranking quality.
In recommender systems, we are often interested in how well method can rank a given set of items. The best possible value is 1, and any non-random ranking that makes sense would have an AUC > 0.5.
An intuitive explanation:
- The AUC specifies the probability that, when we draw two examples at random, their predicted pairwise ranking is correct.
AUC does not give a higher weight to items higher up in the ranking. Some measures that put more weight on higher-ranking items are normalized discounted cumulative gain (NDCG) and mean average precision (MAP).
External links
- Wikipedia: Receiver operating characteristic
- C# implementation of AUC evaluation for binary responses (part of the MyMediaLite library)
