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We discuss interactive techniques for multidimensional scaling (MDS). MDS in its conventional batch implementations is prone to uncertainties with regard to 1) local minima in the underlying optimization, 2) sensitivity to the choice of the optimization criterion, 3) artifacts in point configurations, and 4) local inadequacy of the point configurations. These uncertainties will be addressed by the following interactive techniques: 1) algorithm animation, random restarts, and manual editing of configurations, 2) interactive control over parameters that determine the criterion and its minimization, 3) diagnostics for pinning down artifactual point configurations, and 4) restricting MDS to subsets of objects and subsets of pairs of objects.
A system, called “XGvis”, which implements these techniques, is freely available with the “XGobi” distribution. XGobi is a multivariate data visualization system that is used here for visualizing point configurations.
The final publication is available at Springer via http://dx.doi.org/10.1007/s00357-001-0031-0.
proximity data, multivariate analysis, data visualization, interactive graphics
Buja, A., & Swayne, D. F. (2002). Visualization Methodology for Multidimensional Scaling. Journal of Classification, 19 (1), 7-43. http://dx.doi.org/10.1007/s00357-001-0031-0
Date Posted: 27 November 2017
This document has been peer reviewed.