The analysis of high-dimensional data is an important, yet inherently
difficult problem. Projection techniques such as Principal Component Analysis,
Multi-dimensional Scaling and Self-Organizing Map can be used to map high-dimensional data
to 2D display space. However, projections typically incur a loss in information. Often,
uncertainty exists regarding the precision of the projection as compared with its original
data characteristics. While the output quality of these projection techniques can be
discussed in terms of aggregate numeric error values, visualization is often helpful for
better understanding the projection results. We address the visual assessment of
projection precision by an approach integrating an appropriately designed projection
precision measure directly into the projection visualization. To this end, a flexible
projection precision measure is defined that allows the user to balance the degree of
locality at which the measure is evaluated. S
everal visual mappings are designed for integrating the precision measure into the
projection visualization at various levels of abstraction. The techniques are implemented
in an interactive system, including methods supporting the user in finding appropriate
settings of relevant parameters. We demonstrate the usefulness of the approach for visual
analysis of classified and unclassified high-dimensional data sets. We show how our
interactive precision quality visualization system helps to examine the preservation of
original data properties in projected space.
| 