How to make large self-organizing maps for nonvectorial data

How to make large self-organizing maps for nonvectorial data
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DOI:
10.1016/s0893-6080(02)00069-2
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发表时间:
2002-10-01
期刊:
影响因子:
7.8
通讯作者:
Somervuo, P
Somervuo, P
中科院分区:
计算机科学1区
文献类型:
--
作者:
Kohonen, T;Somervuo, P

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自组织映射(SOM)表示一组开放的输入样本的拓扑组织,有限的模型集。在本文中,一个新版本的SOM用于聚类,组织和可视化的符号序列(即蛋白质序列)的大型数据库。该方法结合了两个原则:SOM的批处理计算版本和符号串的广义中值的计算。(C)2002爱思唯尔科技有限公司版权所有。
The self-organizing map (SOM) represents an open set of input samples by a topologically organized, finite set of models. In this paper, a new version of the SOM is used for the clustering, organization, and visualization of a large database of symbol sequences (viz. protein sequences). This method combines two principles: the batch computing version of the SOM, and computation of the generalized median of symbol strings. (C) 2002 Elsevier Science Ltd. All rights reserved.