So sánh phương pháp

	Độ chính xác	Độ chính xác cân bằng	Ma trận nhầm lẫn
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM	MCDM
Năm ra đời	20th century	2010	20th century
Người khởi xướng	Historical statistical foundations	Brodersen, Ong, Stephan, and Buhmann	Statistical foundations
Loại	Evaluation metric	Evaluation metric	Evaluation visualization
Công trình gốc	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010). The balanced accuracy and its posterior distribution. 20th International Conference on Pattern Recognition (ICPR), 3121-3124.	Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC.
Tên gọi khác	Overall Accuracy, Correct Classification Rate	Average Recall, Equal-weight Average Sensitivity	Error Matrix, Contingency Table
Liên quan	5	5	5
Tóm tắt	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.	Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regardless of class frequency in the dataset.	The confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics.