Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Specificiteit× | Matthews Correlatiecoëfficiënt× | |
|---|---|---|
| Vakgebied | Modelevaluatie | Modelevaluatie |
| Familie | MCDM | MCDM |
| Jaar van ontstaan≠ | 20th century | 1975 |
| Grondlegger≠ | Historical statistical foundations | Brian W. Matthews |
| Type | Evaluation metric | Evaluation metric |
| Oorspronkelijke bron≠ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ | 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 ↗ |
| Aliassen | True Negative Rate, TNR | Phi Coefficient, Binary Classification Correlation |
| Verwant | 5 | 5 |
| Samenvatting≠ | Specificity measures the proportion of actual negative cases that were correctly identified as negative by the classifier. It answers the question: 'Of all the cases that were truly negative, how many did we correctly reject?' Specificity is complementary to recall and is essential when false positives are costly. | 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. |
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