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Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.

Atcerēšanās (jutība)×Specifiskums×
NozareModeļu novērtēšanaModeļu novērtēšana
SaimeMCDMMCDM
Izcelsmes gads20th century20th century
AutorsHistorical statistical foundationsHistorical statistical foundations
TipsEvaluation metricEvaluation metric
PirmavotsFawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
Citi nosaukumiSensitivity, True Positive Rate, TPRTrue Negative Rate, TNR
Saistītās55
KopsavilkumsRecall measures the proportion of actual positive cases that were correctly identified by the classifier. It answers the question: 'Of all the cases that were truly positive, how many did we find?' Recall is critical in scenarios where missing positive cases is costly.Specificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are costly.
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ScholarGateSalīdzināt metodes: Recall (Sensitivity) · Specificity. Izgūts 2026-06-15 no https://scholargate.app/lv/compare