विधियों की तुलना करें

	सटीकता	स्मरण (संवेदनशीलता)
क्षेत्र	मॉडल मूल्यांकन	मॉडल मूल्यांकन
परिवार	MCDM	MCDM
उद्भव वर्ष	20th century	20th century
प्रवर्तक	Historical statistical foundations	Historical statistical foundations
प्रकार	Evaluation metric	Evaluation metric
मौलिक स्रोत	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.
उपनाम	Overall Accuracy, Correct Classification Rate	Sensitivity, True Positive Rate, TPR
संबंधित	5	5
सारांश	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.	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.