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Spectral methods for growth curve clustering

Author

Listed:
  • Snježana Majstorović

    (J.J. Strossmayer University of Osijek)

  • Kristian Sabo

    (J.J. Strossmayer University of Osijek)

  • Johannes Jung

    (Technical University of Berlin)

  • Matija Klarić

    (J.J. Strossmayer University of Osijek)

Abstract

The growth curve clustering problem is analyzed and its connection with the spectral relaxation method is described. For a given set of growth curves and similarity function, a similarity matrix is defined, from which the corresponding similarity graph is constructed. It is shown that a nearly optimal growth curve partition can be obtained from the eigendecomposition of a specific matrix associated with a similarity graph. The results are illustrated and analyzed on the set of synthetically generated growth curves. One real-world problem is also given.

Suggested Citation

  • Snježana Majstorović & Kristian Sabo & Johannes Jung & Matija Klarić, 2018. "Spectral methods for growth curve clustering," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 715-737, September.
    • Handle: RePEc:spr:cejnor:v:26:y:2018:i:3:d:10.1007_s10100-017-0515-6
    DOI: 10.1007/s10100-017-0515-6
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    References listed on IDEAS

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    Cited by:

    1. Marijana Zekić-Sušac & Rudolf Scitovski & Goran Lešaja, 2018. "CEJOR special issue of Croatian Operational Research Society," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 531-534, September.

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