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Matriu de confusió×Recordació (Sensibilitat)×
CampAvaluació de modelsAvaluació de models
FamíliaMCDMMCDM
Any d'origen20th century20th century
Autor originalStatistical foundationsHistorical statistical foundations
TipusEvaluation visualizationEvaluation metric
Font seminalEveritt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
ÀliesError Matrix, Contingency TableSensitivity, True Positive Rate, TPR
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.Recall 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.
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ScholarGateCompara mètodes: Confusion Matrix · Recall (Sensitivity). Recuperat el 2026-06-17 de https://scholargate.app/ca/compare