Võrdle meetodeid

	Täpsus	Täpsus
Valdkond	Mudelite hindamine	Mudelite hindamine
Perekond	MCDM	MCDM
Tekkeaasta	20th century	20th century
Looja	Historical statistical foundations	Historical statistical foundations
Tüüp	Evaluation metric	Evaluation metric
Algallikas	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.
Rööpnimetused	Overall Accuracy, Correct Classification Rate	Positive Predictive Value, PPV
Seotud	5	5
Kokkuvõte	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.	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.