A Study on Two-stage Self-Organizing Map and Its Application to Clustering Problems

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  • ２段階ＳＯＭの提案とそのクラスタリング問題への適用
  • 2 ダンカイ SOM ノ テイアン ト ソノ クラスタリング モンダイ エ ノ テキヨウ

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This paper presents a two-stage self-organizing map algorithm what we call Two-stage SOM which combines Kohonen's basic SOM (BSOM) and Aoki's SOM with threshold operation (THSOM). In the first stage of Two-stage SOM, we use BSOM algorithm in order to acquire topological structure of input data, and then we apply THSOM algorithm so that inactivated code-vectors move to appropriate region reflecting the distribution of the input data. Furthermore, we show that Two-stage SOM can be applied to clustering problems. Some experimental results reveal that Two-stage SOM is effective for clustering problems in comparison with conventional methods.

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