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Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Citlivost (senzitivita)×Přesnost×
OborHodnocení modelůHodnocení modelů
RodinaMCDMMCDM
Rok vzniku20th century20th century
TvůrceHistorical statistical foundationsHistorical statistical foundations
TypEvaluation metricEvaluation metric
Původní zdrojFawcett, 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 ↗
Další názvySensitivity, True Positive Rate, TPRPositive Predictive Value, PPV
Příbuzné55
ShrnutíRecall 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.Precision 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.
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ScholarGatePorovnat metody: Recall (Sensitivity) · Precision. Získáno 2026-06-15 z https://scholargate.app/cs/compare