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Tačnost×Odziv (Osetljivost)×
OblastEvaluacija modelaEvaluacija modela
PorodicaMCDMMCDM
Godina nastanka20th century20th century
TvoracHistorical statistical foundationsHistorical statistical foundations
TipEvaluation metricEvaluation metric
Temeljni izvorFawcett, 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 ↗
Drugi naziviOverall Accuracy, Correct Classification RateSensitivity, True Positive Rate, TPR
Srodne55
SažetakAccuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class.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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ScholarGateUporedite metode: Accuracy · Recall (Sensitivity). Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare