A Survey on Recent Advances in Self-Organizing Maps
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866929676500336640 |
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| author | Guérin, Axel Chauvet, Pierre Saubion, Frédéric |
| author_facet | Guérin, Axel Chauvet, Pierre Saubion, Frédéric |
| contents | Self-organising maps are a powerful tool for cluster analysis in a wide range of data contexts. From the pioneer work of Kohonen, many variants and improvements have been proposed. This review focuses on the last decade, in order to provide an overview of the main evolution of the seminal SOM algorithm as well as of the methodological developments that have been achieved in order to better fit to various application contexts and users' requirements. We also highlight a specific and important application field that is related to commercial use of SOM, which involves specific data management. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_08416 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Survey on Recent Advances in Self-Organizing Maps Guérin, Axel Chauvet, Pierre Saubion, Frédéric Neural and Evolutionary Computing Artificial Intelligence Self-organising maps are a powerful tool for cluster analysis in a wide range of data contexts. From the pioneer work of Kohonen, many variants and improvements have been proposed. This review focuses on the last decade, in order to provide an overview of the main evolution of the seminal SOM algorithm as well as of the methodological developments that have been achieved in order to better fit to various application contexts and users' requirements. We also highlight a specific and important application field that is related to commercial use of SOM, which involves specific data management. |
| title | A Survey on Recent Advances in Self-Organizing Maps |
| topic | Neural and Evolutionary Computing Artificial Intelligence |
| url | https://arxiv.org/abs/2501.08416 |