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Koefisien Korelasi Matthews×Skor F1×Kepersisan×
BidangPenilaian ModelPenilaian ModelPenilaian Model
KeluargaMCDMMCDMMCDM
Tahun asal1975197920th century
PengasasBrian W. MatthewsC. J. van RijsbergenHistorical statistical foundations
JenisEvaluation 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 MeanPositive Predictive Value, PPV
Berkaitan555
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.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.
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ScholarGateBandingkan kaedah: Matthews Correlation Coefficient · F1-Score · Precision. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare