Lazy Self-Organizing Map and its Behaviors

被引：0

作者：

Haraguchi, Taku ^{[1
]}

Matsushita, Haruna ^{[1
]}

Nishio, Yoshifumi ^{[1
]}

机构：

[1] Univ Tokushima, Dept Elect & Engn, Tokushima 770, Japan

来源：

2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8 | 2008年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Self-Organizing Map (SOM) is a famous algorithm for the unsupervised learning and visualization introduced by Teuvo Kohonen. This study proposes the Lazy Self-Organizing Map (LSOM) algorithm which reflects the world of worker ants. In LSOM, three kinds of neurons exist: worker neurons, lazy neurons and indecisive neurons. We apply LSOM to various input data set and contirm that LSOM can obtain a more effective map reflecting the distribution state of the input data than the conventional SOM.

引用

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页码：2275 / 2280

页数：6

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