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| Matrica zabune× | Preciznost× | |
|---|---|---|
| Područje | Evaluacija modela | Evaluacija modela |
| Obitelj | MCDM | MCDM |
| Godina nastanka | 20th century | 20th century |
| Tvorac≠ | Statistical foundations | Historical statistical foundations |
| Vrsta≠ | Evaluation visualization | Evaluation metric |
| Temeljni izvor≠ | 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 ↗ |
| Drugi nazivi | Error Matrix, Contingency Table | Positive Predictive Value, PPV |
| Srodne | 5 | 5 |
| Sažetak≠ | 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. |
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