University of Hertfordshire

By the same authors

Semi-supervised construction of general visualization hierarchies

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Original languageEnglish
Title of host publicationIn: Proceedings of the 2002 International Conference on Artificial Intelligence - (IC-AI'02)
EditorsH.R. Arabnia, Y. Mun
PublisherCSREA Press
Pages1380-1386
Publication statusPublished - 2002

Abstract

We have recently developed a principled
approach to interactive non-linear hierarchical
visualization [8] based on the Generative Topographic
Mapping (GTM). Hierarchical plots are
needed when a single visualization plot is not sufficient
(e.g. when dealing with large quantities of
data). In this paper we extend our system by giving
the user a choice of initializing the child plots of
the current plot in either interactive, or automatic
mode. In the interactive mode the user interactively
selects “regions of interest” as in [8], whereas in the
automatic mode an unsupervised minimum message
length (MML)-driven construction of a mixture of
GTMs is used. The latter is particularly useful
when the plots are covered with dense clusters of
highly overlapping data projections, making it difficult
to use the interactive mode. Such a situation
often arises when visualizing large data sets. We
illustrate our approach on a data set of 2300 18-
dimensional points and mention extension of our
system to accommodate discrete data types.

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