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Space-Filling Curve: A Robust Data Mining Tool

  • Valentin OwczarekEmail author
  • Patrick Franco
  • Rémy Mullot
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1069)

Abstract

Due to the development of internet and the intensive social network communications, the number of data grows exponentially in our society. In response, we need tools to discover structures in multidimensional data. In that context, dimensionality reduction techniques are useful because they make it possible to visualize high dimension phenomena in low dimensional space. Space-filling curves is an alternative to regular techniques, for example, principal component analysis (PCA). One interesting aspect of this alternative is the computing time required (less than half a second where PCA spends seconds). Moreover with the algorithms provide results are comparable with PCA in term of data visualization. Intensive experiments are led to characterize this new alternative on several dataset covering complex data behaviors.

Keywords

Dimension reduction Data visualization Space-filing curves 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Valentin Owczarek
    • 1
    Email author
  • Patrick Franco
    • 1
  • Rémy Mullot
    • 1
  1. 1.La Rochelle Université, Laboratoire Informatique, Image et Interaction (L3i)La RochelleFrance

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