{"title":"A Consideration on the multi-dimensional topology in Self-Organizing Maps","authors":"Kikuo Fujimura, Kazuhiro Masuda, Yutaka Fukui","doi":"10.1109/ISPACS.2006.364772","DOIUrl":null,"url":null,"abstract":"The 1-dimensional topological network (line) and 2-dimensional topological network (2D-plane) of self-organizing Maps are well used for many applications. We propose the 3-dimensional topological self-organizing maps and give suggestion of an ability of more higher dimensional Maps. Since a compression ratio becomes low by 3-dimensional SOM as compared with 2-dimensional SOM, it may be able to leave more information on the original data. Research of 3- dimensional SOM is not popular. The main reasons are 1) The topology of units has various patterns and 2) The general-purpose topology which can be used in common with many data sets is not established. The data visualization technique of having been suitable for 3-dimensional SOM is proposed in this paper.","PeriodicalId":178644,"journal":{"name":"2006 International Symposium on Intelligent Signal Processing and Communications","volume":"320 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Symposium on Intelligent Signal Processing and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPACS.2006.364772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The 1-dimensional topological network (line) and 2-dimensional topological network (2D-plane) of self-organizing Maps are well used for many applications. We propose the 3-dimensional topological self-organizing maps and give suggestion of an ability of more higher dimensional Maps. Since a compression ratio becomes low by 3-dimensional SOM as compared with 2-dimensional SOM, it may be able to leave more information on the original data. Research of 3- dimensional SOM is not popular. The main reasons are 1) The topology of units has various patterns and 2) The general-purpose topology which can be used in common with many data sets is not established. The data visualization technique of having been suitable for 3-dimensional SOM is proposed in this paper.