Salīdzināt metodes

	F1-novērtējums	Makro vidējais F1
Nozare	Modeļu novērtēšana	Modeļu novērtēšana
Saime	MCDM	MCDM
Izcelsmes gads	1979	2000s
Autors	C. J. van Rijsbergen	Multi-class evaluation community
Tips	Evaluation metric	Evaluation metric
Pirmavots	van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann.	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.
Citi nosaukumi	F-measure, Harmonic Mean	Macro F1, Unweighted average F1
Saistītās	5	3
Kopsavilkums	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.	Macro-averaged F1 computes the F1-score independently for each class and then takes the unweighted arithmetic mean. It treats all classes equally, regardless of their frequency in the dataset, making it useful for imbalanced multi-class problems.