Порівняння методів

	F1-Score	Втрати Геммінга
Галузь	Оцінювання моделей	Оцінювання моделей
Родина	MCDM	MCDM
Рік появи	1979	2000s
Автор методу	C. J. van Rijsbergen	Information theory and multi-label learning
Тип	Evaluation metric	Loss function
Основоположне джерело	van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann.	Schapire, R. E., & Singer, Y. (2000). BoosTexter: A boosting-based system for text categorization. Machine Learning, 39(2-3), 135-168.
Інші назви	F-measure, Harmonic Mean	Hamming Distance, Subset Accuracy Loss
Пов'язані	5	1
Підсумок	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.	Hamming loss measures the fraction of labels that are incorrectly predicted in multi-label classification. It counts the number of label mistakes divided by the total number of labels, providing a simple metric for multi-label problems.