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Præcision×Specificitet×
FagområdeModelevalueringModelevaluering
FamilieMCDMMCDM
Oprindelsesår20th century20th century
OphavspersonHistorical statistical foundationsHistorical statistical foundations
TypeEvaluation metricEvaluation metric
Oprindelig kildeFawcett, 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 ↗
AliasserPositive Predictive Value, PPVTrue Negative Rate, TNR
Relaterede55
ResuméPrecision measures the proportion of positive predictions that were actually correct. It answers the question: 'Of all the cases we predicted as positive, how many were truly positive?' Precision is critical in scenarios where false positives are 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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ScholarGateSammenlign metoder: Precision · Specificity. Hentet 2026-06-15 fra https://scholargate.app/da/compare