Compară metode

	Analiza ROC (Caracteristica Operativă a Receptorului)	Analiza discriminantă
Domeniu	Statistică	Statistică
Familie	Hypothesis test	Latent structure
Anul apariției	1954 (signal detection); 1982 (AUC formalization)	1936
Autorul original	Peterson, Birdsall & Fox (signal detection theory); Hanley & McNeil (medical statistics)	Ronald A. Fisher
Tip	Diagnostic accuracy evaluation	Supervised classification and dimension reduction
Sursa seminală	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.
Denumiri alternative	ROC curve analysis, AUC analysis, sensitivity-specificity analysis, diagnostic accuracy analysis	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Înrudite	4	4
Rezumat	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.