قارن الطرق

	مقياس F-beta	مقياس F1 المُعدّل كليًا
المجال	تقييم النماذج	تقييم النماذج
العائلة	MCDM	MCDM
سنة النشأة	1979	2000s
صاحب الطريقة	C. J. van Rijsbergen	Multi-class evaluation community
النوع	Evaluation metric	Evaluation metric
المصدر التأسيسي	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.
الأسماء البديلة	F-measure with parameter beta	Macro F1, Unweighted average F1
ذات صلة	5	3
الملخص	The F-beta score is a weighted harmonic mean of precision and recall that allows customizing the relative importance of recall versus precision through a parameter beta. It generalizes the F1-score, which is the special case where beta = 1.	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.