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Skor-F1×Koefisien Korelasi Matthews×Presisi×
BidangEvaluasi ModelEvaluasi ModelEvaluasi Model
KeluargaMCDMMCDMMCDM
Tahun asal1979197520th century
PencetusC. J. van RijsbergenBrian W. MatthewsHistorical statistical foundations
TipeEvaluation metricEvaluation metricEvaluation metric
Sumber perintisvan Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗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. DOI ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
AliasF-measure, Harmonic MeanPhi Coefficient, Binary Classification CorrelationPositive Predictive Value, PPV
Terkait555
RingkasanThe 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.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.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 metode: F1-Score · Matthews Correlation Coefficient · Precision. Diakses 2026-06-18 dari https://scholargate.app/id/compare