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| Macierz pomyłek× | Dokładność (Accuracy)× | |
|---|---|---|
| Dziedzina | Ocena modeli | Ocena modeli |
| Rodzina | MCDM | MCDM |
| Rok powstania | 20th century | 20th century |
| Twórca≠ | Statistical foundations | Historical statistical foundations |
| Typ≠ | Evaluation visualization | Evaluation metric |
| Źródło pierwotne≠ | 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 ↗ |
| Inne nazwy | Error Matrix, Contingency Table | Overall Accuracy, Correct Classification Rate |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | 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. | Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class. |
| ScholarGateZbiór danych ↗ |
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