手法を比較

	ROC分析（受信者操作特性曲線）	判別分析
分野	統計学	統計学
系統	Hypothesis test	Latent structure
提唱年	1954 (signal detection); 1982 (AUC formalization)	1936
提唱者	Peterson, Birdsall & Fox (signal detection theory); Hanley & McNeil (medical statistics)	Ronald A. Fisher
種類	Diagnostic accuracy evaluation	Supervised classification and dimension reduction
原典	Hanley, J. A., & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29–36.	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.
別名	ROC curve analysis, AUC analysis, sensitivity-specificity analysis, diagnostic accuracy analysis	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
関連	4	4
概要	ROC analysis evaluates how well a continuous or ordinal test variable discriminates between two binary outcome classes. By plotting the true positive rate (sensitivity) against the false positive rate (1 − specificity) across all decision thresholds, it produces a curve whose area under the curve (AUC) quantifies overall discriminative power, ranging from 0.5 (chance) to 1.0 (perfect discrimination).	Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error.