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Analiza skupień×Analiza dyskryminacyjna×
DziedzinaStatystykaStatystyka
RodzinaLatent structureLatent structure
Rok powstania1939–19671936
TwórcaRobert C. Tryon (early development); Ward (1963) for hierarchical; MacQueen (1967) for k-meansRonald A. Fisher
TypUnsupervised classification / groupingSupervised classification and dimension reduction
Źródło pierwotneEveritt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster Analysis (5th ed.). Wiley. ISBN: 978-0470749913Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗
Inne nazwyclustering, unsupervised classification, data clustering, numerical taxonomyLDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Pokrewne54
PodsumowanieCluster analysis is a family of unsupervised multivariate techniques that partition a set of objects or observations into internally homogeneous, mutually distinct groups — clusters — based on measured characteristics, without any prior knowledge of group membership. It is widely used in market segmentation, bioinformatics, psychology, and social science to reveal natural groupings in 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.
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ScholarGatePorównaj metody: Cluster Analysis · Discriminant Analysis. Pobrano 2026-06-17 z https://scholargate.app/pl/compare