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| Точност× | Балансирана точност× | |
|---|---|---|
| Област | Оценка на модели | Оценка на модели |
| Семейство | MCDM | MCDM |
| Година на възникване≠ | 20th century | 2010 |
| Създател≠ | Historical statistical foundations | Brodersen, Ong, Stephan, and Buhmann |
| Тип | Evaluation metric | Evaluation metric |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | Overall Accuracy, Correct Classification Rate | Average Recall, Equal-weight Average Sensitivity |
| Свързани | 5 | 5 |
| Резюме≠ | Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class. | 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. |
| ScholarGateНабор от данни ↗ |
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