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Klusteranalys×Diskriminantanalys×
ÄmnesområdeStatistikStatistik
FamiljLatent structureLatent structure
Ursprungsår1939–19671936
UpphovspersonRobert C. Tryon (early development); Ward (1963) for hierarchical; MacQueen (1967) for k-meansRonald A. Fisher
TypUnsupervised classification / groupingSupervised classification and dimension reduction
UrsprungskällaEveritt, 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 ↗
Aliasclustering, unsupervised classification, data clustering, numerical taxonomyLDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Närliggande54
SammanfattningCluster 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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ScholarGateJämför metoder: Cluster Analysis · Discriminant Analysis. Hämtad 2026-06-17 från https://scholargate.app/sv/compare