swMATH ID: 1963
Software Authors: Samsonova, Elena V.; Kok, Joost N.; Ijzerman, Ad P.
Description: TreeSOM: cluster analysis in the self-organizing map Clustering problems arise in various domains of science and engineering. A large number of methods have been developed to date. The Kohonen self-organizing map (SOM) is a popular tool that maps a high-dimensional space onto a small number of dimensions by placing similar elements close together, forming clusters. Cluster analysis is often left to the user. In this paper we present the method TreeSOM and a set of tools to perform unsupervised SOM cluster analysis, determine cluster confidence and visualize the result as a tree facilitating comparison with existing hierarchical classifiers. We also introduce a distance measure for cluster trees that allows one to select a SOM with the most confident clusters.
Homepage: http://www.sciencedirect.com/science/article/pii/S0893608006000669
Keywords: self-organizing map; hierarchical clustering; tree; reliability; visualization; tool
Related Software: GTM; Tulip; PRMLT; SOM_PAK; ClustalW; PHYLIP; UCI-ml
Referenced in: 4 Publications

Referenced in 1 Field

4 Computer science (68-XX)

Referencing Publications by Year