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Ανάλυση Συμπλεγμάτων×Διερευνητική Ανάλυση Παραγόντων (EFA)×
ΠεδίοΣτατιστικήΣτατιστική
ΟικογένειαLatent structureLatent structure
Έτος προέλευσης1939–1967
ΔημιουργόςRobert C. Tryon (early development); Ward (1963) for hierarchical; MacQueen (1967) for k-means
ΤύποςUnsupervised classification / groupingLatent variable / dimension reduction
Θεμελιώδης πηγήEveritt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster Analysis (5th ed.). Wiley. ISBN: 978-0470749913Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗
Εναλλακτικές ονομασίεςclustering, unsupervised classification, data clustering, numerical taxonomycommon factor analysis, açımlayıcı faktör analizi, factor analysis
Συναφείς54
ΣύνοψηCluster 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.Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.
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ScholarGateΣύγκριση μεθόδων: Cluster Analysis · EFA. Ανακτήθηκε στις 2026-06-15 από https://scholargate.app/el/compare