Interactive Comprehensible Data Mining - Ambient Intelligence for Scientific Discovery - page 51

Fig. 1. A collapsed graph (of Soybean data shaded by class).

sets there needs to be a number of optimizations: only considering the strongest
links, introducing locality of influence and so on.

2.2 Perception-Oriented Visualization

The interface provides full 3D control of the structure, from zooming in and out,
moving smoothly through the system (flyby), rotating it in 3D, and jumping to
specific points, all controlled with the mouse.
Some typical structures emerge, recognizable across many data sets. These
include clusters of similar items, outlying items not in any particular cluster,
and internal structures within perceived clusters. For example, the data may be
seen as divided into two main groups, both of which contain a number of sub-
groups. Examples of data visualization are shown in the case studies (Sections
4.1 and 4.2).

2.3 Interaction with the Data Visualization

When features of interest are seen in the visual representation of the data they
can be selected using the mouse. This opens up a number of possibilities:

- Data identification
- Re-visualization
- Explanation