方法对比

	混淆矩阵	Matthews Correlation Coefficient
领域	模型评估	模型评估
方法族	MCDM	MCDM
起源年份	20th century	1975
提出者	Statistical foundations	Brian W. Matthews
类型	Evaluation visualization	Evaluation metric
开创性文献	Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC.	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.
别名	Error Matrix, Contingency Table	Phi Coefficient, Binary Classification Correlation
相关	5	5
摘要	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.	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.