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A New Feature Extraction Method Based on the Partial Least Squares Algorithm and Its Applications

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Computer Recognition Systems 3

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 57))

Summary

The aim of this paper is to present a new feature extraction method. Our method is an extension of the classical Partial Least Squares (PLS) algorithm. However, a new weighted separation criterion is applied which is based on the within and between scatter matrices. In order to compare the performance of the classification the biological and spam datasets are used.

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References

  1. Blaszczyk, P.: Data classification by using modified partial least squares method. PhD thesis. Silesian University of Technology (2008)

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Author information

Authors and Affiliations

  1. Institute of Mathematics, University of Silesia, Poland

    Pawel Blaszczyk

  2. Institute of Computer Science, Silesian University of Technology, Poland

    Katarzyna Stapor

Authors
  1. Pawel Blaszczyk
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  2. Katarzyna Stapor
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Editor information

Editors and Affiliations

  1. Wroclaw University of Technology, WybrzezeWyspianskiego 27, 50-370, Wroclaw, Poland

    Marek Kurzynski  & Michal Wozniak  & 

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© 2009 Springer-Verlag Berlin Heidelberg

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Blaszczyk, P., Stapor, K. (2009). A New Feature Extraction Method Based on the Partial Least Squares Algorithm and Its Applications. In: Kurzynski, M., Wozniak, M. (eds) Computer Recognition Systems 3. Advances in Intelligent and Soft Computing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93905-4_22

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  • DOI: https://doi.org/10.1007/978-3-540-93905-4_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-93904-7

  • Online ISBN: 978-3-540-93905-4

  • eBook Packages: EngineeringEngineering (R0)

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