Сравнение на методи

	Точност	Прецизност
Област	Оценка на модели	Оценка на модели
Семейство	MCDM	MCDM
Година на възникване	20th century	20th century
Създател	Historical statistical foundations	Historical statistical foundations
Тип	Evaluation metric	Evaluation metric
Основополагащ източник	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.
Други названия	Overall Accuracy, Correct Classification Rate	Positive Predictive Value, PPV
Свързани	5	5
Резюме	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.