방법 비교

	혼동 행렬	정확도
분야	모델 평가	모델 평가
계열	MCDM	MCDM
기원 연도	20th century	20th century
창시자	Statistical foundations	Historical statistical foundations
유형	Evaluation visualization	Evaluation metric
원전	Everitt, B. S., & Hothorn, T. (2005). A Handbook of Statistical Analyses Using R. Chapman and Hall/CRC.	Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874.
별칭	Error Matrix, Contingency Table	Overall Accuracy, Correct Classification Rate
관련	5	5
요약	The confusion matrix is a table that displays the counts of true positives, true negatives, false positives, and false negatives. It provides a complete picture of where a classifier makes correct and incorrect predictions, enabling calculation of all other classification metrics.	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.