Сравнение на методи

	Прецизност	Покритие (Чувствителност)
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	Positive Predictive Value, PPV	Sensitivity, True Positive Rate, TPR
Свързани	5	5
Резюме	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.	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.