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Viacrozmerné škálovanie (MDS)×Korešpondenčná analýza×
OdborŠtatistikaŠtatistika
RodinaLatent structureLatent structure
Rok vzniku1952–19641984
TvorcaWarren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964)Jean-Paul Benzécri; Michael Greenacre
TypDimensionality reduction / visualizationExploratory multivariate technique for categorical data
Pôvodný zdrojKruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27. DOI ↗Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2
Ďalšie názvyMDS, metric MDS, non-metric MDS, proximity scalingCA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi
Príbuzné52
ZhrnutieMultidimensional 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.Correspondence Analysis (CA) is an exploratory multivariate technique for visualizing the association structure of a two-way contingency table. Developed systematically by Jean-Paul Benzécri in France during the 1960s–1970s and brought to an English-language audience by Michael Greenacre in 1984, CA decomposes the chi-square statistic of a cross-tabulation to produce a low-dimensional joint display — called a biplot — in which rows and columns are represented as points whose proximities reflect their associations.
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ScholarGatePorovnať metódy: Multidimensional Scaling · Correspondence Analysis. Získané 2026-06-18 z https://scholargate.app/sk/compare