2011 | OriginalPaper | Buchkapitel
Topographic Mapping of Dissimilarity Data
verfasst von : Barbara Hammer, Andrej Gisbrecht, Alexander Hasenfuss, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu
Erschienen in: Advances in Self-Organizing Maps
Verlag: Springer Berlin Heidelberg
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Topographic mapping offers a very flexible tool to inspect large quantities of high-dimensional data in an intuitive way. Often, electronic data are inherently non-Euclidean and modern data formats are connected to dedicated non-Euclidean dissimilarity measures for which classical topographic mapping cannot be used. We give an overview about extensions of topographic mapping to general dissimilarities by means of median or relational extensions. Further, we discuss efficient approximations to avoid the usually squared time complexity.