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| Statystyka J Youdena× | Zrównoważona dokładność× | Wynik F1× | |
|---|---|---|---|
| Dziedzina | Ocena modeli | Ocena modeli | Ocena modeli |
| Rodzina | MCDM | MCDM | MCDM |
| Rok powstania≠ | 1950 | 2010 | 1979 |
| Twórca≠ | W. J. Youden | Brodersen, Ong, Stephan, and Buhmann | C. J. van Rijsbergen |
| Typ | Evaluation metric | Evaluation metric | Evaluation metric |
| Źródło pierwotne≠ | Youden, W. J. (1950). Index for rating diagnostic tests. Cancer, 3(1), 32-35. 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 ↗ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ |
| Inne nazwy | Youden Index, Sensitivity + Specificity - 1 | Average Recall, Equal-weight Average Sensitivity | F-measure, Harmonic Mean |
| Pokrewne≠ | 3 | 5 | 5 |
| Podsumowanie≠ | Youdens J statistic, also called the Youden index, measures the maximum difference between the true positive rate and false positive rate across different classification thresholds. It is useful for selecting optimal cutoff points in diagnostic testing. | 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 F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important. |
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