Comparar métodos

	Escalamiento multidimensional (MDS)	Análisis discriminante
Campo	Estadística	Estadística
Familia	Latent structure	Latent structure
Año de origen	1952–1964	1936
Autor original	Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964)	Ronald A. Fisher
Tipo	Dimensionality reduction / visualization	Supervised classification and dimension reduction
Fuente seminal	Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27.	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.
Alias	MDS, metric MDS, non-metric MDS, proximity scaling	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Relacionados	5	4
Resumen	Multidimensional scaling maps objects described only by pairwise similarities or dissimilarities into a low-dimensional geometric space so that distances in that space reflect the original proximity structure as faithfully as possible. It is widely used to visualize the hidden structure of psychological, social, and behavioral data.	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.