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Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Matrice de confuzie×Specificitate×
DomeniuEvaluarea modelelorEvaluarea modelelor
FamilieMCDMMCDM
Anul apariției20th century20th century
Autorul originalStatistical foundationsHistorical statistical foundations
TipEvaluation visualizationEvaluation metric
Sursa seminalăEveritt, 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 ↗
Denumiri alternativeError Matrix, Contingency TableTrue Negative Rate, TNR
Înrudite55
RezumatThe 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.
ScholarGateSet de date
  1. v1
  2. 2 Surse
  3. PUBLISHED
  1. v1
  2. 2 Surse
  3. PUBLISHED

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ScholarGateCompară metode: Confusion Matrix · Specificity. Preluat la 2026-06-17 de pe https://scholargate.app/ro/compare