Comparar métodos

	Coeficiente de Correlação de Matthews	F1-Score	Sensibilidade
Área	Avaliação de modelos	Avaliação de modelos	Avaliação de modelos
Família	MCDM	MCDM	MCDM
Ano de origem	1975	1979	20th century
Autor original	Brian W. Matthews	C. J. van Rijsbergen	Historical statistical foundations
Tipo	Evaluation metric	Evaluation metric	Evaluation metric
Fonte seminal	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.	van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
Outros nomes	Phi Coefficient, Binary Classification Correlation	F-measure, Harmonic Mean	Sensitivity, True Positive Rate, TPR
Relacionados	5	5	5
Resumo	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.	The F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important.	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.