Strategies for Multidimensional Data Visualization

  • Gintautas Dzemyda
  • Olga Kurasova
  • Julius Žilinskas
Part of the Springer Optimization and Its Applications book series (SOIA, volume 75)


In this chapter, an analytical review of methods for multidimensional data visualization is presented. The methods based on direct visualization and projections are described. Some quantitative criteria of the visualization quality are also introduced.


Linear Discriminant Analysis Geodesic Distance Multidimensional Data Locally Linear Embedding Laplacian Eigenmaps 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  • Gintautas Dzemyda
    • 1
  • Olga Kurasova
    • 1
  • Julius Žilinskas
    • 1
  1. 1.Institute of Mathematics and InformaticsVilnius UniversityVilniusLithuania

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