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Self-organizing Map Initialization

Mohammed Attik 1, 2 Laurent Bougrain 1 Frédéric Alexandre 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The solution obtained by Self-Organizing Map (SOM) strongly depends on the initial cluster centers. However, all existing SOM initialization methods do not guarantee to obtain a better minimal solution. Generally, we can group these methods in two classes: random initialization and data analysis based initialization classes. This work proposes an improvement of linear projection initialization method. This method belongs to the second initialization class. Instead of using regular rectangular grid our method combines a linear projection technique with irregular rectangular grid. By this way the distribution of results produced by the linear projection technique is considred. The experiments confirm that the proposed method gives better solutions compared to its original version.
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https://hal.inria.fr/inria-00000622
Contributor : Mohammed Attik <>
Submitted on : Thursday, November 10, 2005 - 9:41:19 AM
Last modification on : Friday, February 26, 2021 - 3:28:03 PM

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Mohammed Attik, Laurent Bougrain, Frédéric Alexandre. Self-organizing Map Initialization. 15th International conference on Artificial Neural Networks - ICANN 2005, Sep 2005, Warsaw/Poland, pp.357--362, ⟨10.1007/11550822_56⟩. ⟨inria-00000622⟩

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