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Presisi×Akurasi×
BidangEvaluasi ModelEvaluasi Model
KeluargaMCDMMCDM
Tahun asal20th century20th century
PencetusHistorical statistical foundationsHistorical statistical foundations
TipeEvaluation metricEvaluation metric
Sumber perintisFawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗
AliasPositive Predictive Value, PPVOverall Accuracy, Correct Classification Rate
Terkait55
RingkasanPrecision 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.Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class.
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  2. 2 Sumber
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  1. v1
  2. 2 Sumber
  3. PUBLISHED

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ScholarGateBandingkan metode: Precision · Accuracy. Diakses 2026-06-15 dari https://scholargate.app/id/compare