Visualization of multidimensional data taking into account the learning flow of the self organizing neural network
In the paper we discuss the visualization of multidimensional vectors taking into account the learning flow of the self organizing neural network. A new algorithm realizing a combination of the self-organizing map (SOM) and Sammon's mapping has been proposed. It takes into account the intermed...
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| Format: | Article |
| Language: | English |
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Vilnius University Press
2002-12-01
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| Series: | Lietuvos Matematikos Rinkinys |
| Online Access: | https://www.zurnalai.vu.lt/LMR/article/view/32894 |
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| _version_ | 1825197226858643456 |
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| author | Gintautas Dzemyda Olga Kurasova |
| author_facet | Gintautas Dzemyda Olga Kurasova |
| author_sort | Gintautas Dzemyda |
| collection | DOAJ |
| description |
In the paper we discuss the visualization of multidimensional vectors taking into account the learning flow of the self organizing neural network. A new algorithm realizing a combination of the self-organizing map (SOM) and Sammon's mapping has been proposed. It takes into account the intermediate learning results of the SOM. The experiments showed that the algorithm gives lower average projection errors compared with a consequent application of the SOM and Sammon's mapping.
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| format | Article |
| id | doaj-art-2b36563f21ff4281afa05fe34fd4fb01 |
| institution | Kabale University |
| issn | 0132-2818 2335-898X |
| language | English |
| publishDate | 2002-12-01 |
| publisher | Vilnius University Press |
| record_format | Article |
| series | Lietuvos Matematikos Rinkinys |
| spelling | doaj-art-2b36563f21ff4281afa05fe34fd4fb012025-02-11T18:13:45ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2002-12-0142spec.10.15388/LMR.2002.32894Visualization of multidimensional data taking into account the learning flow of the self organizing neural networkGintautas Dzemyda0Olga Kurasova1Institute of Mathematics and InformaticsInstitute of Mathematics and Informatics In the paper we discuss the visualization of multidimensional vectors taking into account the learning flow of the self organizing neural network. A new algorithm realizing a combination of the self-organizing map (SOM) and Sammon's mapping has been proposed. It takes into account the intermediate learning results of the SOM. The experiments showed that the algorithm gives lower average projection errors compared with a consequent application of the SOM and Sammon's mapping. https://www.zurnalai.vu.lt/LMR/article/view/32894 |
| spellingShingle | Gintautas Dzemyda Olga Kurasova Visualization of multidimensional data taking into account the learning flow of the self organizing neural network Lietuvos Matematikos Rinkinys |
| title | Visualization of multidimensional data taking into account the learning flow of the self organizing neural network |
| title_full | Visualization of multidimensional data taking into account the learning flow of the self organizing neural network |
| title_fullStr | Visualization of multidimensional data taking into account the learning flow of the self organizing neural network |
| title_full_unstemmed | Visualization of multidimensional data taking into account the learning flow of the self organizing neural network |
| title_short | Visualization of multidimensional data taking into account the learning flow of the self organizing neural network |
| title_sort | visualization of multidimensional data taking into account the learning flow of the self organizing neural network |
| url | https://www.zurnalai.vu.lt/LMR/article/view/32894 |
| work_keys_str_mv | AT gintautasdzemyda visualizationofmultidimensionaldatatakingintoaccountthelearningflowoftheselforganizingneuralnetwork AT olgakurasova visualizationofmultidimensionaldatatakingintoaccountthelearningflowoftheselforganizingneuralnetwork |