Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kļūdu matrica× | Atcerēšanās (jutība)× | |
|---|---|---|
| Nozare | Modeļu novērtēšana | Modeļu novērtēšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads | 20th century | 20th century |
| Autors≠ | Statistical foundations | Historical statistical foundations |
| Tips≠ | Evaluation visualization | Evaluation metric |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi≠ | Error Matrix, Contingency Table | Sensitivity, True Positive Rate, TPR |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | 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. |
| ScholarGateDatu kopa ↗ |
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