Bandingkan metode

	Recall (Sensitivitas)	Presisi
Bidang	Evaluasi Model	Evaluasi Model
Keluarga	MCDM	MCDM
Tahun asal	20th century	20th century
Pencetus	Historical statistical foundations	Historical statistical foundations
Tipe	Evaluation metric	Evaluation metric
Sumber perintis	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
Alias	Sensitivity, True Positive Rate, TPR	Positive Predictive Value, PPV
Terkait	5	5
Ringkasan	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.	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.