So sánh phương pháp

	F1-score trung bình vi mô	Độ chính xác
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM
Năm ra đời	2000s	20th century
Người khởi xướng	Multi-class evaluation community	Historical statistical foundations
Loại	Evaluation metric	Evaluation metric
Công trình gốc	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.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
Tên gọi khác	Micro F1, Frequency-weighted average F1	Overall Accuracy, Correct Classification Rate
Liên quan	4	5
Tóm tắt	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.	Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class.