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Точность×Специфичность×
ОбластьОценка моделейОценка моделей
СемействоMCDMMCDM
Год появления20th century20th century
Автор методаHistorical statistical foundationsHistorical statistical foundations
ТипEvaluation metricEvaluation metric
Основополагающий источникFawcett, 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 ↗
Другие названияPositive Predictive Value, PPVTrue Negative Rate, TNR
Связанные55
СводкаPrecision 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.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Precision · Specificity. Получено 2026-06-15 из https://scholargate.app/ru/compare