Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Balansētā precizitāte× | Matjūsa korelasijas koeficients× | |
|---|---|---|
| Nozare | Modeļu novērtēšana | Modeļu novērtēšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 2010 | 1975 |
| Autors≠ | Brodersen, Ong, Stephan, and Buhmann | Brian W. Matthews |
| Tips | Evaluation metric | Evaluation metric |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi | Average Recall, Equal-weight Average Sensitivity | Phi Coefficient, Binary Classification Correlation |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. |
| ScholarGateDatu kopa ↗ |
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