Comparer des méthodes

	Multinomial Logistic Regression	Analyse discriminante
Domaine	Statistique	Statistique
Famille	Regression model	Latent structure
Année d'origine	1966–1974	1936
Auteur d'origine	Cox (1966); Theil (1969); formalized by McFadden (1974)	Ronald A. Fisher
Type	Generalized linear model	Supervised classification and dimension reduction
Source fondatrice	Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Wiley-Interscience. ISBN: 978-0471360933	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.
Alias	polytomous logistic regression, softmax regression, multinomial logit, nominal logistic regression	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Apparentées	4	4
Résumé	Multinomial logistic regression extends binary logistic regression to outcomes with three or more unordered categories. It models the log-odds of each category relative to a chosen reference category as a linear function of the predictors, and estimates all parameters simultaneously via maximum likelihood. It is the standard choice when the dependent variable is nominal with multiple levels.	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.