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Precisión×Especificidad×
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 ↗
AliasPositive Predictive Value, PPVTrue Negative Rate, TNR
Relacionados55
ResumenPrecision 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.Specificity 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.
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: Precision · Specificity. Recuperado el 2026-06-15 de https://scholargate.app/es/compare