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| Wynik F1× | F1 ważona× | |
|---|---|---|
| Dziedzina | Ocena modeli | Ocena modeli |
| Rodzina | MCDM | MCDM |
| Rok powstania≠ | 1979 | 2000s |
| Twórca≠ | C. J. van Rijsbergen | Multi-class evaluation community |
| Typ | Evaluation metric | Evaluation metric |
| Źródło pierwotne≠ | van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗ | 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 ↗ |
| Inne nazwy≠ | F-measure, Harmonic Mean | Support-weighted F1 |
| Pokrewne≠ | 5 | 3 |
| Podsumowanie≠ | 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. | 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. |
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