So sánh phương pháp

	Độ chính xác (Precision)	Độ chính xác	Hệ số Tương quan Matthews
Lĩnh vực	Đánh giá mô hình	Đánh giá mô hình	Đánh giá mô hình
Họ	MCDM	MCDM	MCDM
Năm ra đời	20th century	20th century	1975
Người khởi xướng	Historical statistical foundations	Historical statistical foundations	Brian W. Matthews
Loại	Evaluation metric	Evaluation metric	Evaluation metric
Công trình gốc	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	Matthews, B. W. (1975). Comparison of predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA)-Protein Structure, 405(2), 442-451.
Tên gọi khác	Positive Predictive Value, PPV	Overall Accuracy, Correct Classification Rate	Phi Coefficient, Binary Classification Correlation
Liên quan	5	5	5
Tóm tắt	Precision measures the proportion of positive predictions that were actually correct. It answers the question: 'Of all the cases we predicted as positive, how many were truly positive?' Precision is critical in scenarios where false positives are costly.	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 Matthews Correlation Coefficient (MCC) is a correlation measure between predicted and actual binary classifications. It ranges from -1 to 1 and is considered one of the most reliable single-score metrics for evaluating binary classifiers, especially on imbalanced datasets.