Compara mètodes

	F1 micro-mitjana	Puntuació F1
Camp	Avaluació de models	Avaluació de models
Família	MCDM	MCDM
Any d'origen	2000s	1979
Autor original	Multi-class evaluation community	C. J. van Rijsbergen
Tipus	Evaluation metric	Evaluation metric
Font seminal	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.	van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann.
Àlies	Micro F1, Frequency-weighted average F1	F-measure, Harmonic Mean
Relacionats	4	5
Resum	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.	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.