مقایسهٔ روش‌ها

	بازیابی (حساسیت)	دقت موزون	امتیاز F1
حوزه	ارزیابی مدل	ارزیابی مدل	ارزیابی مدل
خانواده	MCDM	MCDM	MCDM
سال پیدایش	20th century	2010	1979
پدیدآور	Historical statistical foundations	Brodersen, Ong, Stephan, and Buhmann	C. J. van Rijsbergen
نوع	Evaluation metric	Evaluation metric	Evaluation metric
منبع بنیادین	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010). The balanced accuracy and its posterior distribution. 20th International Conference on Pattern Recognition (ICPR), 3121-3124.	van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann.
نام‌های دیگر	Sensitivity, True Positive Rate, TPR	Average Recall, Equal-weight Average Sensitivity	F-measure, Harmonic Mean
مرتبط	5	5	5
خلاصه	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.	Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regardless of class frequency in the dataset.	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.