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| Ανάκληση (Ευαισθησία)× | Σταθμισμένη Ακρίβεια× | |
|---|---|---|
| Πεδίο | Αξιολόγηση Μοντέλων | Αξιολόγηση Μοντέλων |
| Οικογένεια | MCDM | MCDM |
| Έτος προέλευσης≠ | 20th century | 2010 |
| Δημιουργός≠ | Historical statistical foundations | Brodersen, Ong, Stephan, and Buhmann |
| Τύπος | Evaluation metric | Evaluation metric |
| Θεμελιώδης πηγή≠ | 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 ↗ |
| Εναλλακτικές ονομασίες≠ | Sensitivity, True Positive Rate, TPR | Average Recall, Equal-weight Average Sensitivity |
| Συναφείς | 5 | 5 |
| Σύνοψη≠ | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
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