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Punteggio F1×Coefficiente di Correlazione di Matthews×Precisione×
CampoValutazione dei modelliValutazione dei modelliValutazione dei modelli
FamigliaMCDMMCDMMCDM
Anno di origine1979197520th century
IdeatoreC. J. van RijsbergenBrian W. MatthewsHistorical statistical foundations
TipoEvaluation metricEvaluation metricEvaluation metric
Fonte seminalevan 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 ↗
AliasF-measure, Harmonic MeanPhi Coefficient, Binary Classification CorrelationPositive Predictive Value, PPV
Correlati555
SintesiThe 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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ScholarGateConfronta i metodi: F1-Score · Matthews Correlation Coefficient · Precision. Consultato il 2026-06-18 da https://scholargate.app/it/compare