Сравнение методов

	Коэффициент корреляции Мэтьюса	Сбалансированная точность	F1-мера
Область	Оценка моделей	Оценка моделей	Оценка моделей
Семейство	MCDM	MCDM	MCDM
Год появления	1975	2010	1979
Автор метода	Brian W. Matthews	Brodersen, Ong, Stephan, and Buhmann	C. J. van Rijsbergen
Тип	Evaluation metric	Evaluation metric	Evaluation metric
Основополагающий источник	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.	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.
Другие названия	Phi Coefficient, Binary Classification Correlation	Average Recall, Equal-weight Average Sensitivity	F-measure, Harmonic Mean
Связанные	5	5	5
Сводка	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.	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.