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2004
Springer

KMC/EDAM: A New Approach for the Visualization of K-Means Clustering Results

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KMC/EDAM: A New Approach for the Visualization of K-Means Clustering Results
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.
Nils Raabe, Karsten Luebke, Claus Weihs
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where GFKL
Authors Nils Raabe, Karsten Luebke, Claus Weihs
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