Lazy self-organizing map for effective self-organization (非線形問題)
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概要
- 論文の詳細を見る
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 confirm that LSOM can obtain a more effective map reflecting the distribution state of the input data than the conventional SOM.
- 社団法人電子情報通信学会の論文
- 2008-03-21
著者
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NISHIO Yoshifumi
Department of Electrical and Electronic Engineering, Tokushima University
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MATSUSHITA Haruna
Department of Electrical and Electronic Engineering, Tokushima University
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Nishio Yoshifumi
Department Of Dept. Of Electrical And Electronics Engineering Tokushima University
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HARAGUCHI Taku
Department of Electrical and Electronic Engineering, Tokushima University
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Haraguchi Taku
Department Of Electrical And Electronic Engineering Tokushima University
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Matsushita Haruna
Department Of Electrical And Electronic Engineering Tokushima University
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