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Verwarringsmatrix×Specificiteit×
VakgebiedModelevaluatieModelevaluatie
FamilieMCDMMCDM
Jaar van ontstaan20th century20th century
GrondleggerStatistical foundationsHistorical statistical foundations
TypeEvaluation visualizationEvaluation metric
Oorspronkelijke bronEveritt, 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 ↗
AliassenError Matrix, Contingency TableTrue Negative Rate, TNR
Verwant55
SamenvattingThe 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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  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: Confusion Matrix · Specificity. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare