The main purpose of this paper is to demonstrate the data reduction technique of self-organizing maps and to compare it with data reduction techniques in SPSS. Especially, factor analysis and multidimensional scaling (MDS) are chosen. Subsequent to data reduction a cluster analysis was conducted. Due to taking the same cluster algorithm on the base of different data reduction approaches we can compare the final outputs of the cluster algorithm in respect to a target criterion. This is the homogeneity within the groups compared to the homogeneity between the groups. The application example is taken from literature (Backhaus et al. 1994).
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:16320 |
Date | 21 September 2017 |
Creators | Löbler, Helge, Buchholz, Petra, Petersohn, Helge |
Contributors | Universität Leipzig |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/acceptedVersion, doc-type:workingPaper, info:eu-repo/semantics/workingPaper, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
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