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Konfusionsmatrix×Recall (Sensitivität)×
FachgebietModellevaluationModellevaluation
FamilieMCDMMCDM
Entstehungsjahr20th century20th century
UrheberStatistical foundationsHistorical statistical foundations
TypEvaluation visualizationEvaluation metric
Wegweisende QuelleEveritt, 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 ↗
AliasnamenError Matrix, Contingency TableSensitivity, True Positive Rate, TPR
Verwandt55
ZusammenfassungThe 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.Recall 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.
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ScholarGateMethoden vergleichen: Confusion Matrix · Recall (Sensitivity). Abgerufen am 2026-06-18 von https://scholargate.app/de/compare