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| Uravnotežena točnost× | Preciznost× | |
|---|---|---|
| Područje | Evaluacija modela | Evaluacija modela |
| Obitelj | MCDM | MCDM |
| Godina nastanka≠ | 2010 | 20th century |
| Tvorac≠ | Brodersen, Ong, Stephan, and Buhmann | Historical statistical foundations |
| Vrsta | Evaluation metric | Evaluation metric |
| Temeljni izvor≠ | 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 ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| Drugi nazivi | Average Recall, Equal-weight Average Sensitivity | Positive Predictive Value, PPV |
| Srodne | 5 | 5 |
| Sažetak≠ | 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. | Precision measures the proportion of positive predictions that were actually correct. It answers the question: 'Of all the cases we predicted as positive, how many were truly positive?' Precision is critical in scenarios where false positives are costly. |
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