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Matrix visualisation for high-dimensional data with a cartography link

Chun-houh Chen (Institute of statistical science, Academia Sinica, Taiwan; web)
Úterý 14. května 2013, 14:20 hodin
Didaktický kabinet KMD (4. patro budovy H areálu TUL, Voroněžská 1329/13, Liberec 1, č. dv. 5027)
Organizuje Katedra aplikované matematiky
[Pozvánka v PDF]

Anotace

Matrix visualization (MV) is more efficient than conventional graphical tools such as scatterplot, boxplot, and parallel-coordinate-plot in extracting information structure embedded in high-dimensional continuous data. For noncontinuous data, conventional tools cannot provide much visual information while categorical MV gives us information about interaction of subject-clusters on variable-groups for up to thousands of subjects with thousands of categorical variables in a single display. When an cartography link is attached to each subject of a high-dimensional categorical data, it is necessary 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.