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Análisis discriminante×Regresión Logística×
CampoEstadísticaEstadística para la investigación
FamiliaLatent structureProcess / pipeline
Año de origen19361958
Autor originalRonald A. FisherDavid Roxbee Cox
TipoSupervised classification and dimension reductionMethod
Fuente seminalFisher, 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
Relacionados43
ResumenDiscriminant 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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  3. PUBLISHED

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ScholarGateComparar métodos: Discriminant Analysis · Logistic Regression. Recuperado el 2026-06-18 de https://scholargate.app/es/compare