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| Matrice di confusione× | Precisione× | |
|---|---|---|
| Campo | Valutazione dei modelli | Valutazione dei modelli |
| Famiglia | MCDM | MCDM |
| Anno di origine | 20th century | 20th century |
| Ideatore≠ | Statistical foundations | Historical statistical foundations |
| Tipo≠ | Evaluation visualization | Evaluation metric |
| Fonte seminale≠ | Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC. link ↗ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ |
| Alias | Error Matrix, Contingency Table | Positive Predictive Value, PPV |
| Correlati | 5 | 5 |
| Sintesi≠ | The confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics. | 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. |
| ScholarGateInsieme di dati ↗ |
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