Artefactual structure from least squares multidimensional scaling

Abstract

We consider the problem of illusory or artefactual structure from the visualisation of high-dimensional structureless data. In particular we examine the role of the distance metric in the use of topographic mappings based on the statistical field of multidimensional scaling. We show that the use of a squared Euclidean metric (i.e. the SSTRESs measure) gives rise to an annular structure when the input data is drawn from a high-dimensional isotropic distribution, and we provide a theoretical justification for this observation.

Divisions: College of Engineering & Physical Sciences > Mathematics
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Event Title: 16th Annual Neural Information Processing Systems Conference, NIPS 2002
Event Type: Other
Event Dates: 2002-12-09 - 2002-12-14
Uncontrolled Keywords: Problem of illusory,artefactual structure,visualisation,high-dimensional structureless data,topographic mappings,squared Euclidean metric,high-dimensional isotropic distribution,Computer Networks and Communications,Information Systems,Signal Processing
ISBN: 0262025507, 9780262025508
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2003
Authors: Hughes, Nicholas P.
Lowe, David

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Version: Accepted Version


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