|
Activity Number:
|
523
|
|
Type:
|
Invited
|
|
Date/Time:
|
Thursday, August 2, 2007 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
IMS
|
| Abstract - #308000 |
|
Title:
|
Matrix Visualization for High-Dimensional Categorical Data Structure with a Cartography Link
|
|
Author(s):
|
Chun-houh Chen*+ and Sheng Li Tzeng and Chiun-How Kao
|
|
Companies:
|
Academia Sinica and Academia Sinica and Academia Sinica
|
|
Address:
|
Institute of Statistical Science, Taipei, International, 115, Taiwan
|
|
Keywords:
|
categorical data ; color coding ; homogeneity analysis ; geographic visualization ; proximity measure
|
|
Abstract:
|
Matrix visualization (MV) is more efficient than conventional graphical tools such as scatterplot, boxplot, and parallel-coordinate-plot in extracting information structure embedded in moderate (hundreds) to high dimensional continuous data. For non-continuous data, conventional tools can not provide much visual information while MV gives us information about individual profiles with interaction of subject-clusters on variable-groups. When an cartography link is attached to each sample of a high-dimensional categorical data matrix, it is desired to use a geographical map to illustrate the pattern of subject (region)-clusters with variable-groups embedded in the high-dimensional space. This study presents an interactive cartography system with systematic color coding by integrating the homogeneity analysis into matrix visualization. For more information see: http://gap.stat.sinica.edu.tw.
|
