Identification of noisy variables for nonmetric and symbolic data in cluster analysis
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| dc.contributor.author | Walesiak, Marek | |
|---|---|---|
| dc.contributor.author | Dudek, Andrzej | |
| dc.contributor.organization | Uniwersytet Ekonomiczny we Wrocławiu | en |
| dc.date.accessioned | 2013-03-09T22:20:25Z | |
| dc.date.available | 2013-03-09T22:20:25Z | |
| dc.date.issued | 2008 | |
| dc.description.abstract | A proposal of an extended version of the HINoV method for the iden- tification of the noisy variables (Carmone et al [1999]) for nonmetric, mixed, and symbolic interval data is presented in this paper. Proposed modifications are eval- uated on simulated data from a variety of models. The models contain the known structure of clusters. In addition, the models contain a different number of noisy (irrelevant) variables added to obscure the underlying structure to be recovered. | en |
| dc.description.eperson | Marek Walesiak | |
| dc.identifier.isbn | 978-3-540-78239-1 | |
| dc.identifier.issn | 1431-8814 | |
| dc.identifier.uri | https://open.icm.edu.pl/handle/123456789/1049 | |
| dc.language.iso | en | en |
| dc.publisher | Springer-Verlag | en |
| dc.rights | Dozwolony użytek | |
| dc.subject | clusterSim | en |
| dc.subject | nonmetric and symbolic data | en |
| dc.subject | HINoV method | en |
| dc.subject | variable selection | en |
| dc.title | Identification of noisy variables for nonmetric and symbolic data in cluster analysis | en |
| dc.type | article | en |
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