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Dimensionality Problem in the Visualization of Correlation-Based Data

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Adaptive and Natural Computing Algorithms (ICANNGA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4432))

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Abstract

A method for visualization the correlation-based data has been investigated. The advantage of this method lies in the possibility to restore the system of multidimensional vectors describing parameters from their correlation matrix (one vector for one parameter) and to visualise these vectors for the visual decision making on the similarity of the parameters. The goal of this research is to investigate the possibility to reduce the dimensionality of the vectors from the restored system and to evaluate the visualization quality in dependence on the reduction level.

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Authors and Affiliations

  1. Institute of Mathematics and Informatics, Akademijos St. 4, LT 08663, Vilnius,  

    Gintautas Dzemyda & Olga Kurasova

  2. Vilnius Pedagogical University, Studentu St. 39, LT 08106, Vilnius, Lithuania

    Gintautas Dzemyda & Olga Kurasova

Authors
  1. Gintautas Dzemyda
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  2. Olga Kurasova
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Editor information

Bartlomiej Beliczynski Andrzej Dzielinski Marcin Iwanowski Bernardete Ribeiro

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Dzemyda, G., Kurasova, O. (2007). Dimensionality Problem in the Visualization of Correlation-Based Data. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71629-7_61

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  • DOI: https://doi.org/10.1007/978-3-540-71629-7_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71590-0

  • Online ISBN: 978-3-540-71629-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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