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Koefisien Korelasi Matthews×Skor-F1×Recall (Sensitivitas)×
BidangEvaluasi ModelEvaluasi ModelEvaluasi Model
KeluargaMCDMMCDMMCDM
Tahun asal1975197920th century
PencetusBrian W. MatthewsC. J. van RijsbergenHistorical statistical foundations
TipeEvaluation metricEvaluation metricEvaluation metric
Sumber perintisMatthews, 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. DOI ↗van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
AliasPhi Coefficient, Binary Classification CorrelationF-measure, Harmonic MeanSensitivity, True Positive Rate, TPR
Terkait555
RingkasanThe 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.
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ScholarGateBandingkan metode: Matthews Correlation Coefficient · F1-Score · Recall (Sensitivity). Diakses 2026-06-18 dari https://scholargate.app/id/compare