The Exploration Machine – A Novel Method for Data Visualization

  • Axel Wismüller
Conference paper

DOI: 10.1007/978-3-642-02397-2_39

Volume 5629 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Wismüller A. (2009) The Exploration Machine – A Novel Method for Data Visualization. In: Príncipe J.C., Miikkulainen R. (eds) Advances in Self-Organizing Maps. WSOM 2009. Lecture Notes in Computer Science, vol 5629. Springer, Berlin, Heidelberg

Abstract

We present a novel method for structure-preserving dimensionality reduction. The Exploration Machine (Exploratory Observation Machine, XOM) computes graphical representations of high-dimensional observations by a strategy of self-organized model adaptation. Although simple and computationally efficient, XOM enjoys a surprising flexibility to simultaneously contribute to several different domains of advanced machine learning, scientific data analysis, and visualization, such as structure-preserving dimensionality reduction and data clustering.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Axel Wismüller
    • 1
  1. 1.Depts. of Radiology and Biomedical EngineeringUniversity of RochesterNew YorkU.S.A.