Receiver-operator characteristic curve

{
  "id": "MLC-T-CHM-010008",
  "term": "Receiver-operator characteristic curve",
  "field": "Chemistry",
  "definition": "A graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. It plots the true positive rate (sensitivity) against the false positive rate (1-specificity) at different threshold settings. The area under the curve (AUC) provides a single scalar measure of the classifier's overall performance, ranging from 0.5 for random chance to 1.0 for a perfect classifier.",
  "synonyms": [
    "ROC curve"
  ],
  "subject": "Chemistry and Human Health",
  "see_also": [
    "Boltzmann enhanced discrimination of receiver operating characteristic",
    "area under the curve",
    "false positive",
    "true positive"
  ],
  "references": [
    "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)"
  ],
  "url": "https://mlchart.com/terminology/chemistry/receiver-operator-characteristic-curve/"
}