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Tunnistus (herkkyys)×Tarkkuus×
TieteenalaMallien arviointiMallien arviointi
MenetelmäperheMCDMMCDM
Syntyvuosi20th century20th century
KehittäjäHistorical statistical foundationsHistorical statistical foundations
TyyppiEvaluation metricEvaluation metric
AlkuperäislähdeFawcett, 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 ↗
RinnakkaisnimetSensitivity, True Positive Rate, TPRPositive Predictive Value, PPV
Liittyvät55
TiivistelmäRecall 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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ScholarGateVertaile menetelmiä: Recall (Sensitivity) · Precision. Haettu 2026-06-15 osoitteesta https://scholargate.app/fi/compare