Title: receiver-operator characteristic curve
Long Title: IUPAC Gold Book - receiver-operator characteristic curve
DOI: 10.1351/goldbook.11502
Status: current

Definition
A plot that shows the result of a test of the performance of a binary classifier by plotting the fraction of true positives identified versus the fraction of
 false positives as the discrimination threshold is varied.

Notes
1) ROC curves are frequently used to compare different docking/scoring combinations or virtual screening protocols by the retrieval results from seeding a database of inactive molecules with known actives.
2) The area under the ROC curve (AUC) provides a measure of the superiority of the model over random predictions: If the value for the AUC for a ROC curve has the value of \(\pu{0.9\!-\! 1.0}\), the fit is considered excellent, whereas an AUC of \(\pu{0.5}\) suggests that the algorithm has no discriminatory power.
3) This is an example of using area under the curve as a measure of model performance.

Related Terms
- Boltzmann enhanced discrimination of receiver operating characteristic (BEDROC): https://goldbook.iupac.org//terms/view/11416
- area under the curve: https://goldbook.iupac.org//terms/view/11407
- false positives: https://goldbook.iupac.org//terms/view/11445
- true positives: https://goldbook.iupac.org//terms/view/11528

Source
- PAC, 2016, 88, 239. 'Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)' on page 254 (https://doi.org/10.1515/pac-2012-1204)

Other Outputs
- html: https://goldbook.iupac.org/terms/view/11502/html
- json: https://goldbook.iupac.org/terms/view/11502/json
- xml: https://goldbook.iupac.org/terms/view/11502/xml

Citation: Citation: 'receiver-operator characteristic curve' in IUPAC Compendium of Chemical Terminology, 5th ed. International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.11502
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Accessed: 2026-06-20T07:18:56+00:00