השוואת שיטות

	סגוליות (Specificity)	מדד F1	דיוק (Precision)
תחום	הערכת מודלים	הערכת מודלים	הערכת מודלים
משפחה	MCDM	MCDM	MCDM
שנת המקור	20th century	1979	20th century
הוגה השיטה	Historical statistical foundations	C. J. van Rijsbergen	Historical statistical foundations
סוג	Evaluation metric	Evaluation metric	Evaluation metric
מקור מכונן	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
כינויים	True Negative Rate, TNR	F-measure, Harmonic Mean	Positive Predictive Value, PPV
קשורות	5	5	5
תקציר	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.	The F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important.	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.