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On Dissimilarity Measurement In Visualization Of Multidimensional Data

In: Computer Aided Methods In Optimal Design And Operations

Author

Listed:
  • A. ŽILINSKAS

    (Institute of Mathematics and Informatics, VMU, Akademijos str. 4, Vilnius, 08663, Lithuania)

  • A. PODLIPSKYTĖ

    (Institute of Psychophysiology and Rehabilitation Vyduno str. 4, Palanga, 00135, Lithuania)

Abstract

Multidimensional scaling (MDS) is a prospective technique to the visualization and exploratory analysis of multidimensional data. By means of MDS algorithms a two dimensional representation of a set of points in a high dimensional (original) space can be obtained, where distances between the points in the two dimensional embedding space represent dissimilarity of multidimensional points. The latter normally is measured by the Euclidean distance, although the alternative measures can be advantageous. In the present paper we investigate influence of the choice of dissimilarity measure (distances in the original space) to the visualization results.

Suggested Citation

  • A. Žilinskas & A. Podlipskytė, 2006. "On Dissimilarity Measurement In Visualization Of Multidimensional Data," World Scientific Book Chapters, in: I D L Bogle & J Žilinskas (ed.), Computer Aided Methods In Optimal Design And Operations, chapter 16, pages 149-158, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812772954_0016
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