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| Precisione× | Specificità× | |
|---|---|---|
| Campo | Valutazione dei modelli | Valutazione dei modelli |
| Famiglia | MCDM | MCDM |
| Anno di origine | 20th century | 20th century |
| Ideatore | Historical statistical foundations | Historical statistical foundations |
| Tipo | Evaluation metric | Evaluation metric |
| Fonte seminale | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| Alias | Positive Predictive Value, PPV | True Negative Rate, TNR |
| Correlati | 5 | 5 |
| Sintesi≠ | 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. | Specificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are costly. |
| ScholarGateInsieme di dati ↗ |
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