Median Topographic Maps for Biomedical Data Sets

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Abstract. Median clustering extends popular neural data analysis methods such as the self-organizing map or neural gas to general data structures given by a dissimilarity matrix only. This offers flexible and robust global data inspection methods which are particularly suited for a variety of data as occurs in biomedical domains. In this chapter, we give an overview about median clustering and its properties and extensions, with a particular focus on efficient implementations adapted to large scale data analysis.

Barbara Hammer, Alexander Hasenfuss, Fabrice Rossi

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Added	09 Nov 2010
Updated	09 Nov 2010
Type	Conference
Year	2009
Where	DAGSTUHL
Authors	Barbara Hammer, Alexander Hasenfuss, Fabrice Rossi

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Median Topographic Maps for Biomedical Data Sets

DAGSTUHL 2007 | DAGSTUHL 2009 | Data Analysis | Median Clustering | Popular Neural Data |

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