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.
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;
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on
DOI :
10.1109/SCIS-ISIS.2014.7044648
