Semi-supervised construction of general visualization hierarchies

Peter Tino, Yi Sun, Ian T. Nabney

Research output: Unpublished contribution to conferenceUnpublished Conference Paperpeer-review


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.
Original languageEnglish
Number of pages7
Publication statusPublished - 2002
EventInternational Conference on Artificial Intelligence, 2002 -
Duration: 1 Jan 20021 Jan 2002


ConferenceInternational Conference on Artificial Intelligence, 2002


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


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