Neural networks as competitors for methods of data reduction and classification in SPSS

Description

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).

Links & Downloads

1. urn:nbn:de:bsz:15-qucosa2-163207
2. https://ul.qucosa.de/id/qucosa%3A16320
3. https://ul.qucosa.de/api/qucosa%3A16320/attachment/ATT-0/

Tags

neuronale Netze, Klassifikation

neural networks, classification

Additional Fields

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