| dc.contributor.author | Pełka, Marcin | |
| dc.date.accessioned | 2015-06-22T09:37:04Z | |
| dc.date.available | 2015-06-22T09:37:04Z | |
| dc.date.issued | 2013 | |
| dc.identifier.issn | 0208-6018 | |
| dc.identifier.uri | http://hdl.handle.net/11089/10036 | |
| dc.description.abstract | Ensemble approaches based on aggregated models have been applied with success
to discrimination and regression tasks. Nevertheless this approach can be applied to cluster analysis
tasks. Many articles have proved that, by combining different clusterings, an improved solution
can be obtained.
The article presents the possibility of applying ensemble approach based on aggregated models
to cluster symbolic data. The paper presents also presents results of clustering obtained by
applying ensemble approach. | pl_PL |
| dc.description.abstract | Podejście wielomodelowe oparte na agregacji modeli jest z powodzeniem wykorzystywane w
zagadnieniach dyskryminacyjnych i regresyjnych. Niemniej jednak podejście to może zostać także
zastosowane w zagadnieniu klasyfikacji. W wielu artykułach wskazuje się, że połączenie wielu
różnych klasyfikacji pozwala otrzymać lepsze wyniki.
Artykuł przedstawia możliwość zastosowania podejścia wielomodelowego w klasyfikacji danych
symbolicznych. W artykule przedstawiono także wyniki klasyfikacji z wykorzystaniem podejścia
wielomodelowego. | pl_PL |
| dc.language.iso | en | pl_PL |
| dc.publisher | Wydawnictwo Uniwersytetu Łódzkiego | pl_PL |
| dc.relation.ispartofseries | Acta Universitatis Lodziensis. Folia Oeconomica;285 | |
| dc.subject | cluster ensemble | pl_PL |
| dc.subject | co-associacion matrix | pl_PL |
| dc.subject | symbolic data | pl_PL |
| dc.title | Clustering of Symbolic Data with Application of Ensemble Approach | pl_PL |
| dc.title.alternative | Klasyfikacja danych symbolicznych z wykorzystaniem podejścia wielomodelowego | pl_PL |
| dc.type | Article | pl_PL |
| dc.page.number | [89]-95 | pl_PL |
| dc.contributor.authorAffiliation | Wroclaw, University of Economics, Department of Econometrics and Informatics | pl_PL |
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