Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Сбалансированная точность× | Коэффициент корреляции Мэтьюса× | |
|---|---|---|
| Область | Оценка моделей | Оценка моделей |
| Семейство | MCDM | MCDM |
| Год появления≠ | 2010 | 1975 |
| Автор метода≠ | Brodersen, Ong, Stephan, and Buhmann | Brian W. Matthews |
| Тип | Evaluation metric | Evaluation metric |
| 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. DOI ↗ | 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. DOI ↗ |
| Другие названия | Average Recall, Equal-weight Average Sensitivity | Phi Coefficient, Binary Classification Correlation |
| 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 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. |
| ScholarGateНабор данных ↗ |
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