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تحليل منحنى خاصية تشغيل المستقبل (ROC)×تحليل التمييز×
المجالالإحصاءالإحصاء
العائلةHypothesis testLatent structure
سنة النشأة1954 (signal detection); 1982 (AUC formalization)1936
صاحب الطريقةPeterson, Birdsall & Fox (signal detection theory); Hanley & McNeil (medical statistics)Ronald A. Fisher
النوعDiagnostic accuracy evaluationSupervised classification and dimension reduction
المصدر التأسيسيHanley, 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. DOI ↗Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗
الأسماء البديلةROC curve analysis, AUC analysis, sensitivity-specificity analysis, diagnostic accuracy analysisLDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
ذات صلة44
الملخصROC 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.
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ScholarGateقارن الطرق: ROC analysis · Discriminant Analysis. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare