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Diskriminantanalys×Logistisk regression×
ÄmnesområdeStatistikForskningsstatistik
FamiljLatent structureProcess / pipeline
Ursprungsår19361958
UpphovspersonRonald A. FisherDavid Roxbee Cox
TypSupervised classification and dimension reductionMethod
UrsprungskällaFisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
AliasLDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysislogit model, binomial logistic regression, LR
Närliggande43
SammanfattningDiscriminant 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.Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.
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ScholarGateJämför metoder: Discriminant Analysis · Logistic Regression. Hämtad 2026-06-18 från https://scholargate.app/sv/compare