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Tõlgendustabel×Spetsiifilisus×
ValdkondMudelite hindamineMudelite hindamine
PerekondMCDMMCDM
Tekkeaasta20th century20th century
LoojaStatistical foundationsHistorical statistical foundations
TüüpEvaluation visualizationEvaluation metric
AlgallikasEveritt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
RööpnimetusedError Matrix, Contingency TableTrue Negative Rate, TNR
Seotud55
KokkuvõteThe confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics.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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ScholarGateVõrdle meetodeid: Confusion Matrix · Specificity. Loetud 2026-06-17 aadressilt https://scholargate.app/et/compare