Comparing Classifier's Performance Based on Confidence Interval of the ROC

Simple item page
dc.contributor.authorMalach, Tobias
dc.contributor.authorPomenkova, Jitka
dc.coverage.issue3cs
dc.coverage.volume27cs
dc.date.accessioned2018-11-23T09:26:52Z
dc.date.available2018-11-23T09:26:52Z
dc.date.issued2018-09cs
dc.description.abstractThis paper proposes a new methodology for comparing} two performance methods based on confidence interval for the ROC curve. The methods performed and compared are two algorithms for face recognition. The novelty of the paper is three-fold: i) designing a methodology for the comparison of decision making algorithms via confidence intervals of ROC curves; ii) investigating how sample sizes influence the properties of the particular methods; iii) recommendations for a general comparison of decision making algorithms via confidence intervals of ROC curves. To support our conclusions we investigate and demonstrate several approaches for constructing parametric confidence intervals on real data. Thus, we present a non-traditional and reliable way of reporting pattern recognition results using ROC curves with confidence intervals.en
dc.formattextcs
dc.format.extent827-834cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2018 vol. 27, č. 3, s. 827-834. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2018.0827en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/137042
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2018/18_03_0827_0834.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectConfidence intervalen
dc.subjectROC curvesen
dc.subjectface recognitionen
dc.subjectpattern recognitionen
dc.titleComparing Classifier's Performance Based on Confidence Interval of the ROCen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
18_03_0827_0834.pdf
Size:
1.09 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
2018/3