Improving interpretability of multivariate data through rotations of artificial variates
- Authors
- 황선영; 박애미
- 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
- Pages
- 10
- 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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