Median Topographic Maps for Biomedical Data Sets

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.

• Type: Conference
• Year: 2009
• Where: DAGSTUHL
• Authors: Barbara Hammer, Alexander Hasenfuss, Fabrice Rossi
• Keywords: DAGSTUHL 2007, DAGSTUHL 2009, Data Analysis, Median Clustering, Popular Neural Data