ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Полнота (Чувствительность)×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 названияSensitivity, True Positive Rate, TPRTrue Negative Rate, TNR
Связанные55
СводкаRecall 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.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

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: Recall (Sensitivity) · Specificity. Получено 2026-06-15 из https://scholargate.app/ru/compare