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Visualization of Large Data Sets Using MDS Combined with LVQ

  • Antoine Naud
  • Włodzisław Duch
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)

Abstract

A common task in data mining is the visualization of multivariate objects using various methods, allowing human observers to perceive subtle inter-relations in the dataset. Multidimensional scaling (MDS) is a well known technique used for this purpose, but it due to its computational complexity there are limitations on the number of objects that can be displayed. Combining MDS with a clustering method as Learning Vector Quantization allows to obtain displays of large databases that preserve both high accuracy of clustering methods and good visualization properties.

Keywords

Cluster Center Multidimensional Scaling Final Stress Learn Vector Quantization Basis Size 
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-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Antoine Naud
    • 1
  • Włodzisław Duch
    • 1
  1. 1.Department of InformaticsNicholas Copernicus UniversityToruńPoland

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