手法を比較

	多次元尺度構成法 (MDS)	判別分析
分野	統計学	統計学
系統	Latent structure	Latent structure
提唱年	1952–1964	1936
提唱者	Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964)	Ronald A. Fisher
種類	Dimensionality reduction / visualization	Supervised classification and dimension reduction
原典	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.
別名	MDS, metric MDS, non-metric MDS, proximity scaling	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
関連	5	4
概要	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.