Сравнение методов

	Сбалансированная точность	Матрица ошибок
Область	Оценка моделей	Оценка моделей
Семейство	MCDM	MCDM
Год появления	2010	20th century
Автор метода	Brodersen, Ong, Stephan, and Buhmann	Statistical foundations
Тип	Evaluation metric	Evaluation visualization
Основополагающий источник	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.	Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC.
Другие названия	Average Recall, Equal-weight Average Sensitivity	Error Matrix, Contingency Table
Связанные	5	5
Сводка	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 confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics.