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Recall (känslighet)×F1-poäng×Matthews Korrelationskoefficient×
ÄmnesområdeModellutvärderingModellutvärderingModellutvärdering
FamiljMCDMMCDMMCDM
Ursprungsår20th century19791975
UpphovspersonHistorical statistical foundationsC. J. van RijsbergenBrian W. Matthews
TypEvaluation metricEvaluation metricEvaluation metric
UrsprungskällaFawcett, 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 ↗Matthews, B. W. (1975). Comparison of predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA)-Protein Structure, 405(2), 442-451. DOI ↗
AliasSensitivity, True Positive Rate, TPRF-measure, Harmonic MeanPhi Coefficient, Binary Classification Correlation
Närliggande555
SammanfattningRecall 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.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.The Matthews Correlation Coefficient (MCC) is a correlation measure between predicted and actual binary classifications. It ranges from -1 to 1 and is considered one of the most reliable single-score metrics for evaluating binary classifiers, especially on imbalanced datasets.
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ScholarGateJämför metoder: Recall (Sensitivity) · F1-Score · Matthews Correlation Coefficient. Hämtad 2026-06-18 från https://scholargate.app/sv/compare