Сравнение на методи

	Покритие (Чувствителност)	F1-резултат	Коефициент на корелация на Матюс
Област	Оценка на модели	Оценка на модели	Оценка на модели
Семейство	MCDM	MCDM	MCDM
Година на възникване	20th century	1979	1975
Създател	Historical statistical foundations	C. J. van Rijsbergen	Brian W. Matthews
Тип	Evaluation metric	Evaluation metric	Evaluation metric
Основополагащ източник	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.	Matthews, B. W. (1975). Comparison of predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA)-Protein Structure, 405(2), 442-451.
Други названия	Sensitivity, True Positive Rate, TPR	F-measure, Harmonic Mean	Phi Coefficient, Binary Classification Correlation
Свързани	5	5	5
Резюме	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.	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.	The Matthews Correlation Coefficient (MCC) is a correlation measure between predicted and actual binary classifications. It ranges from -1 to 1 and is considered one of the most reliable single-score metrics for evaluating binary classifiers, especially on imbalanced datasets.