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Especificidad×Sensibilidad×
CampoEvaluación de modelosEvaluación de modelos
FamiliaMCDMMCDM
Año de origen20th century20th century
Autor originalHistorical statistical foundationsHistorical statistical foundations
TipoEvaluation metricEvaluation metric
Fuente seminalFawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
AliasTrue Negative Rate, TNRSensitivity, True Positive Rate, TPR
Relacionados55
ResumenSpecificity 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.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.
ScholarGateConjunto de datos
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  2. 2 Fuentes
  3. PUBLISHED
  1. v1
  2. 2 Fuentes
  3. PUBLISHED

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ScholarGateComparar métodos: Specificity · Recall (Sensitivity). Recuperado el 2026-06-15 de https://scholargate.app/es/compare