Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Umahiri (Specificity)× | F1-Score× | |
|---|---|---|
| Nyanja | Tathmini ya Modeli | Tathmini ya Modeli |
| Familia | MCDM | MCDM |
| Mwaka wa asili≠ | 20th century | 1979 |
| Mwanzilishi≠ | Historical statistical foundations | C. J. van Rijsbergen |
| Aina | Evaluation metric | Evaluation metric |
| Chanzo asilia≠ | Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ |
| Majina mbadala | True Negative Rate, TNR | F-measure, Harmonic Mean |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | 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 F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important. |
| ScholarGateSeti ya data ↗ |
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