So sánh phương pháp

	Diện tích Dưới Đường Cong Precision-Recall (PR AUC)	Độ thu hồi (độ nhạy)
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM
Năm ra đời	2006	20th century
Người khởi xướng	Davis and Goadrich	Historical statistical foundations
Loại	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.
Tên gọi khác	PR AUC, PR Curve	Sensitivity, True Positive Rate, TPR
Liên quan	4	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.	Recall measures the proportion of actual positive cases that were correctly identified by the classifier. It answers the question: 'Of all the cases that were truly positive, how many did we find?' Recall is critical in scenarios where missing positive cases is costly.