Visualization methodology for multidimensional scaling

被引:34
作者
Buja, A [1 ]
Swayne, DF
机构
[1] Univ Penn, Wharton Sch, Dept Stat, Philadelphia, PA 19104 USA
[2] AT&T Labs Res, Florham Pk, NJ 07932 USA
关键词
proximity data; multivariate analysis; data visualization; interactive graphics;
D O I
10.1007/s00357-001-0031-0
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We discuss the application of interactive visualization techniques to multidimensional scaling (MDS). MDS in its conventional batch implementations is prone to uncertainties with regard to (a) local minima in the underlying optimization, (b) sensitivity to the choice of the optimization criterion, (c) artifacts in point configurations, and (d) local inadequacy of the point configurations. These uncertainties will be addressed by the following interactive techniques: (a) algorithm animation, random restarts, and manual editing of configurations, (b) interactive control over parameters that determine the criterion and its minimization, (c) diagnostics for pinning down artifactual point configurations, and (d) 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.
引用
收藏
页码:7 / 43
页数:37
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