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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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
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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| Summary: | 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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| ISSN: | 0132-2818 2335-898X |