Semi-supervised construction of general visualization hierarchies

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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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Original languageEnglish
Pages1-7
Number of pages7
StatePublished - 2002
EventInternational Conference on Artificial Intelligence, 2002 -

Conference

ConferenceInternational Conference on Artificial Intelligence, 2002
Period1/01/021/01/02

    Keywords

  • hierarchical visualization, Generative Topographic Mapping, interactive mode, automatic mode, overlapping data projections

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