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| Score F-bêta× | Rappel (Sensibilité)× | |
|---|---|---|
| Domaine | Évaluation de modèles | Évaluation de modèles |
| Famille | MCDM | MCDM |
| Année d'origine≠ | 1979 | 20th century |
| Auteur d'origine≠ | C. J. van Rijsbergen | Historical statistical foundations |
| Type | Evaluation metric | Evaluation metric |
| Source fondatrice≠ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| Alias≠ | F-measure with parameter beta | Sensitivity, True Positive Rate, TPR |
| Apparentées | 5 | 5 |
| Résumé≠ | The F-beta score is a weighted harmonic mean of precision and recall that allows customizing the relative importance of recall versus precision through a parameter beta. It generalizes the F1-score, which is the special case where beta = 1. | 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. |
| ScholarGateJeu de données ↗ |
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