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Discovering Main Vertexical Planes in a Multivariate Data Space by Using CPL Functions

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Advances in Data Mining. Applications and Theoretical Aspects (ICDM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8557))

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Abstract

Data mining problems and tools are linked to the task of extracting important regularities (patterns) from multivariate data sets. In some cases, flat patterns can be located on vertexical planes in a multidimensional data space. Vertexical planes are linked to vertices in parameter space. Patterns located on vertexical planes can be discovered in large data sets through minimization of the convex and piecewise linear (CPL) criterion functions.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland

    Leon Bobrowski

Authors
  1. Leon Bobrowski
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Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

    Petra Perner

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Bobrowski, L. (2014). Discovering Main Vertexical Planes in a Multivariate Data Space by Using CPL Functions. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2014. Lecture Notes in Computer Science(), vol 8557. Springer, Cham. https://doi.org/10.1007/978-3-319-08976-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-08976-8_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08975-1

  • Online ISBN: 978-3-319-08976-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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