Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Citlivost (senzitivita)× | Vyvážená přesnost× | Matthewsův korelační koeficient× | |
|---|---|---|---|
| Obor | Hodnocení modelů | Hodnocení modelů | Hodnocení modelů |
| Rodina | MCDM | MCDM | MCDM |
| Rok vzniku≠ | 20th century | 2010 | 1975 |
| Tvůrce≠ | Historical statistical foundations | Brodersen, Ong, Stephan, and Buhmann | Brian W. Matthews |
| Typ | Evaluation metric | Evaluation metric | Evaluation metric |
| Původní zdroj≠ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. 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 ↗ | 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 ↗ |
| Další názvy≠ | Sensitivity, True Positive Rate, TPR | Average Recall, Equal-weight Average Sensitivity | Phi Coefficient, Binary Classification Correlation |
| Příbuzné | 5 | 5 | 5 |
| Shrnutí≠ | 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. | 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. |
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