Editing Receiver operating characteristic (section)

== History ==
The ROC curve was first developed by electrical engineers and radar engineers during World War II for detecting enemy objects in battlefields, starting in 1941, which led to its name ("receiver operating characteristic").<ref>{{Cite journal |date=May 3, 2024 |title= ROC Solid: Receiver Operator Characteristic (ROC) Curves as a Foundation for Better Diagnostic Tests|pmc= 6022965|last1= Junge|first1= M. R.|last2= Dettori|first2= J. R.|journal= Global Spine Journal|volume= 8|issue= 4|pages= 424–429|doi= 10.1177/2192568218778294|pmid= 29977728}}</ref>

It was soon introduced to [[psychology]] to account for the perceptual detection of stimuli. ROC analysis has been used in [[medicine]], [[radiology]], [[biometrics]], [[forecasting]] of [[natural hazard]]s,<ref>{{Cite journal|last1=Peres|first1=D. J.|last2=Cancelliere|first2=A.|date=2014-12-08|title=Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach|journal=Hydrol. Earth Syst. Sci.|volume=18|issue=12|pages=4913–4931|doi=10.5194/hess-18-4913-2014|issn=1607-7938|bibcode=2014HESS...18.4913P|doi-access=free}}</ref> [[meteorology]],<ref>{{Cite journal|last=Murphy|first=Allan H.|date=1996-03-01|title=The Finley Affair: A Signal Event in the History of Forecast Verification|journal=Weather and Forecasting|volume=11|issue=1|pages=3–20|doi=10.1175/1520-0434(1996)011<0003:tfaase>2.0.co;2|issn=0882-8156|bibcode=1996WtFor..11....3M|doi-access=free}}</ref> model performance assessment,<ref>{{Cite journal|last1=Peres|first1=D. J.|last2=Iuppa|first2=C.|last3=Cavallaro|first3=L.|last4=Cancelliere|first4=A.|last5=Foti|first5=E.|date=2015-10-01|title=Significant wave height record extension by neural networks and reanalysis wind data|journal=Ocean Modelling|volume=94|pages=128–140|doi=10.1016/j.ocemod.2015.08.002|bibcode=2015OcMod..94..128P}}</ref> and other areas for many decades and is increasingly used in [[machine learning]] and [[data mining]] research.