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Preciznost×F1-mera×Odziv (Osetljivost)×
OblastEvaluacija modelaEvaluacija modelaEvaluacija modela
PorodicaMCDMMCDMMCDM
Godina nastanka20th century197920th century
TvoracHistorical statistical foundationsC. J. van RijsbergenHistorical statistical foundations
TipEvaluation metricEvaluation metricEvaluation metric
Temeljni izvorFawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
Drugi naziviPositive Predictive Value, PPVF-measure, Harmonic MeanSensitivity, True Positive Rate, TPR
Srodne555
SažetakPrecision 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.The F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important.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: Precision · F1-Score · Recall (Sensitivity). Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare