השוואת שיטות

	דיוק (Precision)	עֶרְכָּה (רגישות)
תחום	הערכת מודלים	הערכת מודלים
משפחה	MCDM	MCDM
שנת המקור	20th century	20th century
הוגה השיטה	Historical statistical foundations	Historical statistical foundations
סוג	Evaluation metric	Evaluation metric
מקור מכונן	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.
כינויים	Positive Predictive Value, PPV	Sensitivity, True Positive Rate, TPR
קשורות	5	5
תקציר	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.