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F1 makro-purata×Skor F1×
BidangPenilaian ModelPenilaian Model
KeluargaMCDMMCDM
Tahun asal2000s1979
PengasasMulti-class evaluation communityC. J. van Rijsbergen
JenisEvaluation metricEvaluation metric
Sumber perintisPowers, D. M. (2011). Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies, 2(1), 37-63. link ↗van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗
AliasMacro F1, Unweighted average F1F-measure, Harmonic Mean
Berkaitan35
RingkasanMacro-averaged F1 computes the F1-score independently for each class and then takes the unweighted arithmetic mean. It treats all classes equally, regardless of their frequency in the dataset, making it useful for imbalanced multi-class problems.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.
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ScholarGateBandingkan kaedah: Macro-averaged F1 · F1-Score. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare