KMC/EDAM : A new approach for the visualization of K-Means Clustering results - Claus Weihs; Karsten Luebke; Nils Raabe (Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, 2004)
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.
Keywords: 519