Methoden vergleichen
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| Gewichteter F1-Score× | Mikro-gemittelter F1-Wert× | |
|---|---|---|
| Fachgebiet | Modellevaluation | Modellevaluation |
| Familie | MCDM | MCDM |
| Entstehungsjahr | 2000s | 2000s |
| Urheber | Multi-class evaluation community | Multi-class evaluation community |
| Typ | Evaluation metric | Evaluation metric |
| Wegweisende Quelle | 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 ↗ | 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 ↗ |
| Aliasnamen≠ | Support-weighted F1 | Micro F1, Frequency-weighted average F1 |
| Verwandt≠ | 3 | 4 |
| Zusammenfassung≠ | 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. | Micro-averaged F1 computes the F1-score by aggregating true positives, false positives, and false negatives across all classes, then calculating a single metric. It is equivalent to accuracy in multi-class classification and is useful when class distributions reflect their natural importance. |
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