A Consideration on the multi-dimensional topology in Self-Organizing Maps

Kikuo Fujimura, Kazuhiro Masuda, Yutaka Fukui
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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.
关于自组织映射中多维拓扑的思考
自组织映射的一维拓扑网络(线)和二维拓扑网络(二维平面)在许多应用中得到了很好的应用。提出了三维拓扑自组织映射,并提出了高维自组织映射的能力。由于与二维SOM相比,三维SOM的压缩比变得低,因此它可能能够在原始数据上留下更多信息。三维SOM的研究并不流行。主要原因是:1)单元的拓扑结构具有多种模式;2)没有建立起可以与许多数据集共同使用的通用拓扑结构。本文提出了一种适用于三维SOM的数据可视化技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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