Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Gewogen F1× | F1-score× | |
|---|---|---|
| Vakgebied | Modelevaluatie | Modelevaluatie |
| Familie | MCDM | MCDM |
| Jaar van ontstaan≠ | 2000s | 1979 |
| Grondlegger≠ | Multi-class evaluation community | C. J. van Rijsbergen |
| Type | Evaluation metric | Evaluation metric |
| Oorspronkelijke bron≠ | Powers, D. M. (2011). Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies, 2(1), 37-63. link ↗ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ |
| Aliassen≠ | Support-weighted F1 | F-measure, Harmonic Mean |
| Verwant≠ | 3 | 5 |
| Samenvatting≠ | Weighted F1 computes the F1-score for each class and then takes a weighted average, where weights are proportional to the number of samples in each class (support). It provides a middle ground between macro and micro-averaging. | 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. |
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