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Simultaneous Display of Front and Back Sides of Spherical SOM for Health Data Analysis

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Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (WSOM 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 976))

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Abstract

We propose to simultaneously display the front and back sides of the spherical SOM so that cluster locations can be expressed in terms of phase relations even if they are on opposite sides of the spherical SOM. The technique is showcased on the medical health care-data. Furthermore, the component map was converted numerically (DIM (Dimensional Interaction Map) mode) for the medical data case and the result compared with that obtained with the front and back sides of the map.

T. Heizo and O. Masaaki—Emeritus Professor.

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References

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Acknowledgement

We sincerely thankful to Prof. M. V. Hulle of KU Leuven for correcting our English.

Author information

Authors and Affiliations

  1. GAUSS, Inc., Tokyo, Japan

    Niina Gen

  2. Tottori University, Tottori, Japan

    Tokutaka Heizo & Ohkita Masaaki

  3. Fuji-Ikiiki Hospital, Fuji, Japan

    Kasezawa Nobuhiko

Authors
  1. Niina Gen
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  2. Tokutaka Heizo
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  3. Ohkita Masaaki
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  4. Kasezawa Nobuhiko
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Corresponding author

Correspondence to Tokutaka Heizo .

Editor information

Editors and Affiliations

  1. Department of Computer Science, UPC BarcelonaTech, Barcelona, Spain

    Alfredo Vellido

  2. Knowledge Engineering and Machine Learning Group (KEMLG) at Intelligent Data Science and Artificial Intelligence Research Center, UPC BarcelonaTech, Barcelona, Spain

    Karina Gibert

  3. Department of Automatic Control, UPC BarcelonaTech, Barcelona, Spain

    Cecilio Angulo

  4. Departament d'Enginyeria Electrònica, Universitat de València, Burjassot, Valencia, Spain

    José David Martín Guerrero

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Gen, N., Heizo, T., Masaaki, O., Nobuhiko, K. (2020). Simultaneous Display of Front and Back Sides of Spherical SOM for Health Data Analysis. In: Vellido, A., Gibert, K., Angulo, C., Martín Guerrero, J. (eds) Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization. WSOM 2019. Advances in Intelligent Systems and Computing, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-030-19642-4_33

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