• DocumentCode
    3563630
  • Title

    The new proposal of the calculation for the significance degree by once SOM learning — Using iris, gene, and Tof-SIMS data

  • Author

    Oyabu, M. ; Tokutaka, H. ; Ohkita, M. ; Seno, M. ; Ohki, M.

  • fYear
    2014
  • Firstpage
    1114
  • Lastpage
    1119
  • Abstract
    The significance degree of each component was calculated only by once SOM learning where the Spherical Self-Organizing-Map (SSOM) was used for the demonstration. The method can also be used by the usual planar SOM. In the method, kinds of specimens of the data are inserted in each column as each specimen. The method is first demonstrated using the iris data.
  • Keywords
    biology computing; data handling; eye; genetics; learning (artificial intelligence); secondary ion mass spectra; self-organising feature maps; statistical distributions; time of flight mass spectra; Tof-SIMS data; gene; iris data; once SOM learning; planar SOM; significance degree; spherical self-organizing-map; Breast cancer; Fatigue; Gaussian distribution; Iris; Proposals; Self-organizing feature maps; Vectors; Self organizing map; Significance degree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on
  • Type

    conf

  • DOI
    10.1109/SCIS-ISIS.2014.7044648
  • Filename
    7044648