So sánh phương pháp

	Diện tích Dưới Đường Cong Precision-Recall (PR AUC)	Độ chính xác	Điểm F1
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM	MCDM
Năm ra đời	2006	20th century	1979
Người khởi xướng	Davis and Goadrich	Historical statistical foundations	C. J. van Rijsbergen
Loại	Evaluation metric	Evaluation metric	Evaluation metric
Công trình gốc	Davis, J., & Goadrich, M. (2006). The relationship between precision-recall and ROC curves. Proceedings of the 23rd International Conference on Machine Learning, 233-240.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann.
Tên gọi khác	PR AUC, PR Curve	Overall Accuracy, Correct Classification Rate	F-measure, Harmonic Mean
Liên quan	4	5	5
Tóm tắt	The Precision-Recall Area Under the Curve (PR AUC) is the area under the curve formed by plotting recall on the x-axis and precision on the y-axis. It is particularly useful for evaluating classifiers on imbalanced datasets, where it is often more informative than ROC AUC.	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.	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.