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Matriu de confusió×Coeficient de Correlació de Matthews×
CampAvaluació de modelsAvaluació de models
FamíliaMCDMMCDM
Any d'origen20th century1975
Autor originalStatistical foundationsBrian W. Matthews
TipusEvaluation visualizationEvaluation metric
Font seminalEveritt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. 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 ↗
ÀliesError Matrix, Contingency TablePhi Coefficient, Binary Classification Correlation
Relacionats55
ResumThe confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics.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: Confusion Matrix · Matthews Correlation Coefficient. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare