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| Współczynnik korelacji Matthews’a× | Zrównoważona dokładność× | |
|---|---|---|
| Dziedzina | Ocena modeli | Ocena modeli |
| Rodzina | MCDM | MCDM |
| Rok powstania≠ | 1975 | 2010 |
| Twórca≠ | Brian W. Matthews | Brodersen, Ong, Stephan, and Buhmann |
| Typ | Evaluation metric | Evaluation metric |
| Źródło pierwotne≠ | 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 ↗ | 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 ↗ |
| Inne nazwy | Phi Coefficient, Binary Classification Correlation | Average Recall, Equal-weight Average Sensitivity |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | 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. |
| ScholarGateZbiór danych ↗ |
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