Σύγκριση μεθόδων

	Ακρίβεια (Precision)	Ανάκληση (Ευαισθησία)
Πεδίο	Αξιολόγηση Μοντέλων	Αξιολόγηση Μοντέλων
Οικογένεια	MCDM	MCDM
Έτος προέλευσης	20th century	20th century
Δημιουργός	Historical statistical foundations	Historical statistical foundations
Τύπος	Evaluation metric	Evaluation metric
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	Positive Predictive Value, PPV	Sensitivity, True Positive Rate, TPR
Συναφείς	5	5
Σύνοψη	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.	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.