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| Præcision× | Genkald (Sensitivitet)× | |
|---|---|---|
| Fagområde | Modelevaluering | Modelevaluering |
| Familie | MCDM | MCDM |
| Oprindelsesår | 20th century | 20th century |
| Ophavsperson | Historical statistical foundations | Historical statistical foundations |
| Type | Evaluation metric | Evaluation metric |
| Oprindelig kilde | 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 ↗ |
| Aliasser≠ | Positive Predictive Value, PPV | Sensitivity, True Positive Rate, TPR |
| Relaterede | 5 | 5 |
| Resumé≠ | 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. | 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. |
| ScholarGateDatasæt ↗ |
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