Methoden vergleichen

	Recall (Sensitivität)	Präzision
Fachgebiet	Modellevaluation	Modellevaluation
Familie	MCDM	MCDM
Entstehungsjahr	20th century	20th century
Urheber	Historical statistical foundations	Historical statistical foundations
Typ	Evaluation metric	Evaluation metric
Wegweisende Quelle	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
Aliasnamen	Sensitivity, True Positive Rate, TPR	Positive Predictive Value, PPV
Verwandt	5	5
Zusammenfassung	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.	Precision 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.