Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Multinomial Logistic Regression× | Análisis discriminante× | |
|---|---|---|
| Campo | Estadística | Estadística |
| Familia≠ | Regression model | Latent structure |
| Año de origen≠ | 1966–1974 | 1936 |
| Autor original≠ | Cox (1966); Theil (1969); formalized by McFadden (1974) | Ronald A. Fisher |
| Tipo≠ | Generalized linear model | Supervised classification and dimension reduction |
| Fuente seminal≠ | 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. DOI ↗ |
| Alias | polytomous logistic regression, softmax regression, multinomial logit, nominal logistic regression | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis |
| Relacionados | 4 | 4 |
| Resumen≠ | 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. |
| ScholarGateConjunto de datos ↗ |
|
|