Parallelization in combining the SOM and Sammon's mapping
In this paper, we propose a parallel algorithm for multidimensional data visualization combining the neural network (the self-organizing map-SOM) and Sammon’s mapping. Here n-dimensional vectors are projected onto the plane by using Sammon’s mapping taking into account the learning flow of the SOM....
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Vilnius University Press
2003-12-01
|
| Series: | Lietuvos Matematikos Rinkinys |
| Online Access: | https://www.journals.vu.lt/LMR/article/view/32403 |
| _version_ | 1826861901736312832 |
|---|---|
| author | Gintautas Dzemyda Olga Kurasova Virginijus Marcinkevičius |
| author_facet | Gintautas Dzemyda Olga Kurasova Virginijus Marcinkevičius |
| author_sort | Gintautas Dzemyda |
| collection | DOAJ |
| description |
In this paper, we propose a parallel algorithm for multidimensional data visualization combining the neural network (the self-organizing map-SOM) and Sammon’s mapping. Here n-dimensional vectors are projected onto the plane by using Sammon’s mapping taking into account the learning flow of the SOM. It is necessary to investigate some important factors that influence the efficiency of the parallel algorithm. The results of investigation allow us to optimize the number of the SOM training epochs, the number of the SOM training blocks, and the number of Sammon’s iterations.
|
| first_indexed | 2024-03-07T15:39:19Z |
| format | Article |
| id | doaj.art-1e7e89c237044e9786f7613f474281be |
| institution | Directory Open Access Journal |
| issn | 0132-2818 2335-898X |
| language | English |
| last_indexed | 2025-02-16T20:30:16Z |
| publishDate | 2003-12-01 |
| publisher | Vilnius University Press |
| record_format | Article |
| series | Lietuvos Matematikos Rinkinys |
| spelling | doaj.art-1e7e89c237044e9786f7613f474281be2025-01-20T18:17:51ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2003-12-0143spec.10.15388/LMR.2003.32403Parallelization in combining the SOM and Sammon's mappingGintautas Dzemyda0Olga Kurasova1Virginijus Marcinkevičius2Institute of Mathematics and InformaticsInstitute of Mathematics and InformaticsInstitute of Mathematics and Informatics In this paper, we propose a parallel algorithm for multidimensional data visualization combining the neural network (the self-organizing map-SOM) and Sammon’s mapping. Here n-dimensional vectors are projected onto the plane by using Sammon’s mapping taking into account the learning flow of the SOM. It is necessary to investigate some important factors that influence the efficiency of the parallel algorithm. The results of investigation allow us to optimize the number of the SOM training epochs, the number of the SOM training blocks, and the number of Sammon’s iterations. https://www.journals.vu.lt/LMR/article/view/32403 |
| spellingShingle | Gintautas Dzemyda Olga Kurasova Virginijus Marcinkevičius Parallelization in combining the SOM and Sammon's mapping Lietuvos Matematikos Rinkinys |
| title | Parallelization in combining the SOM and Sammon's mapping |
| title_full | Parallelization in combining the SOM and Sammon's mapping |
| title_fullStr | Parallelization in combining the SOM and Sammon's mapping |
| title_full_unstemmed | Parallelization in combining the SOM and Sammon's mapping |
| title_short | Parallelization in combining the SOM and Sammon's mapping |
| title_sort | parallelization in combining the som and sammon s mapping |
| url | https://www.journals.vu.lt/LMR/article/view/32403 |
| work_keys_str_mv | AT gintautasdzemyda parallelizationincombiningthesomandsammonsmapping AT olgakurasova parallelizationincombiningthesomandsammonsmapping AT virginijusmarcinkevicius parallelizationincombiningthesomandsammonsmapping |