Methoden vergleichen

	Multinomiale logistische Regression	Diskriminanzanalyse
Fachgebiet	Statistik	Statistik
Familie	Regression model	Latent structure
Entstehungsjahr	1966–1974	1936
Urheber	Cox (1966); Theil (1969); formalized by McFadden (1974)	Ronald A. Fisher
Typ	Generalized linear model	Supervised classification and dimension reduction
Wegweisende Quelle	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.
Aliasnamen	polytomous logistic regression, softmax regression, multinomial logit, nominal logistic regression	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Verwandt	4	4
Zusammenfassung	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.