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	Ketepatan	Koefisien Korelasi Matthews
Bidang	Penilaian Model	Penilaian Model
Keluarga	MCDM	MCDM
Tahun asal	20th century	1975
Pengasas	Historical statistical foundations	Brian W. Matthews
Jenis	Evaluation metric	Evaluation metric
Sumber perintis	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.
Alias	Overall Accuracy, Correct Classification Rate	Phi Coefficient, Binary Classification Correlation
Berkaitan	5	5
Ringkasan	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.