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| Matrice di confusione× | Coefficiente di Correlazione di Matthews× | |
|---|---|---|
| Campo | Valutazione dei modelli | Valutazione dei modelli |
| Famiglia | MCDM | MCDM |
| Anno di origine≠ | 20th century | 1975 |
| Ideatore≠ | Statistical foundations | Brian W. Matthews |
| 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 ↗ | Matthews, B. W. (1975). Comparison of predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA)-Protein Structure, 405(2), 442-451. DOI ↗ |
| Alias | Error Matrix, Contingency Table | Phi Coefficient, Binary Classification Correlation |
| 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. | The Matthews Correlation Coefficient (MCC) is a correlation measure between predicted and actual binary classifications. It ranges from -1 to 1 and is considered one of the most reliable single-score metrics for evaluating binary classifiers, especially on imbalanced datasets. |
| ScholarGateInsieme di dati ↗ |
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