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	Precision	Noggrannhet
Ämnesområde	Modellutvärdering	Modellutvärdering
Familj	MCDM	MCDM
Ursprungsår	20th century	20th century
Upphovsperson	Historical statistical foundations	Historical statistical foundations
Typ	Evaluation metric	Evaluation metric
Ursprungskälla	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	Positive Predictive Value, PPV	Overall Accuracy, Correct Classification Rate
Närliggande	5	5
Sammanfattning	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.	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.