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F1-Score×Matthews-Korrelationskoeffizient×Präzision×
FachgebietModellevaluationModellevaluationModellevaluation
FamilieMCDMMCDMMCDM
Entstehungsjahr1979197520th century
UrheberC. J. van RijsbergenBrian W. MatthewsHistorical statistical foundations
TypEvaluation metricEvaluation metricEvaluation metric
Wegweisende Quellevan 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 ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
AliasnamenF-measure, Harmonic MeanPhi Coefficient, Binary Classification CorrelationPositive Predictive Value, PPV
Verwandt555
ZusammenfassungThe 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.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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ScholarGateMethoden vergleichen: F1-Score · Matthews Correlation Coefficient · Precision. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare