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arXiv · 0909.0638

Median topographic maps for biomedical data sets

Barbara Hammer·Alexander Hasenfuß·Fabrice Rossi
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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.

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Barbara Hammer, Alexander Hasenfuß, Fabrice Rossi. 2009-09-03. Median topographic maps for biomedical data sets. https://doi.org/10.1007/978-3-642-01805-3_6

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