KMC/EDAM: A new approach for the visualization of K-Means Clustering results

dc.contributor.author	Luebke, Karsten	de
dc.contributor.author	Raabe, Nils	de
dc.contributor.author	Weihs, Claus	de
dc.date.accessioned	2005-01-31T08:15:02Z
dc.date.available	2005-01-31T08:15:02Z
dc.date.issued	2004	de
dc.description.abstract	In this work we introduce a method for classification and visualization. In contrast to simultaneous methods like e.g. Kohonen SOM this new approach, called KMC/EDAM, runs through two stages. In the first stage the data is clustered by classical methods like K-means clustering. In the second stage the centroids of the obtained clusters are visualized in a fixed target space which is directly comparable to that of SOM.	en
dc.format.extent	231705 bytes
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/2003/20079
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-5317
dc.language.iso	en	de
dc.publisher	Universität Dortmund	de
dc.subject.ddc	310	de
dc.title	KMC/EDAM: A new approach for the visualization of K-Means Clustering results	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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