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Especificitat×Coeficient de Correlació de Matthews×
CampAvaluació de modelsAvaluació de models
FamíliaMCDMMCDM
Any d'origen20th century1975
Autor originalHistorical statistical foundationsBrian W. Matthews
TipusEvaluation metricEvaluation metric
Font seminalFawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗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 ↗
ÀliesTrue Negative Rate, TNRPhi Coefficient, Binary Classification Correlation
Relacionats55
ResumSpecificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are costly.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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ScholarGateCompara mètodes: Specificity · Matthews Correlation Coefficient. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare