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Improving interpretability of multivariate data through rotations of artificial variates

Authors
황선영박애미
Issue Date
Jun-2004
Publisher
한국데이터정보과학회
Keywords
Artificial variable; Interpretation; Varimax rotation; Artificial variable; Interpretation; Varimax rotation
Citation
한국데이터정보과학회지, v.15, no.2, pp.297 - 306
Journal Title
한국데이터정보과학회지
Volume
15
Number
2
Start Page
297
End Page
306
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/9613
ISSN
1598-9402
Abstract
It is usual that multivariate data analysis produces related (small number of) artificial variates for data reduction. Among them, refer to MDS(multidimensional scaling), MDPREF(multidimensional preference analysis), CDA(canonical discriminant analysis), CCA(canonical correlation analysis) and FA(factor analysis). Varimax rotation of artificial variables which is originally invented in FA for easy interpretations is applied to diverse multivariate techniques mentioned above. Real data analysisis is performed in order to manifest that rotation improves interpretations of artificial variables.
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