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Proceedings Paper

Method for visualization of multivariate data in a lower dimension
Author(s): Boris M. Igelnik
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Paper Abstract

This paper describes a method for visualization of multivariate data in a lower dimension, primarily in 2D. The method, called Distance Conservation with Filtering (DCF), creates a parameterized mapping of a data set in a lower dimension. Special functions, called filters, extract the most important pairs of points with distances between them to be preserved. A particular construction of a filter and the corresponding algorithm for learning the mapping parameters are described in detail. The DCF is favorably compared with other visualization methods on a number of data sets.

Paper Details

Date Published: 3 May 2001
PDF: 12 pages
Proc. SPIE 4302, Visual Data Exploration and Analysis VIII, (3 May 2001); doi: 10.1117/12.424926
Show Author Affiliations
Boris M. Igelnik, Case Western Reserve Univ. (United States)

Published in SPIE Proceedings Vol. 4302:
Visual Data Exploration and Analysis VIII
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Craig M. Wittenbrink; Matti Grohn, Editor(s)

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