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Descripción
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| Currently, there exist many research areas that produce large multivariable datasets that are difficult to visualize in order to extract useful information. Kohonen self-organizing maps have been used successfully in the visualization and analysis of multidimensional data. In this work, a projection technique that compresses multidimensional datasets into two dimensional space using growing self-organizing maps is described. With this embedding scheme, traditional Kohonen visualization methods have been implemented using growing cell structures networks. New graphical map displays have been compared with Kohonen graphs using two groups of simulated data and one group of real multidimensional data selected from a satellite scene. | |
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Internacional
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Si |
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Nombre congreso
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Intenational Conference on Artificial Neural Networks (IWANN 07) |
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Tipo de participación
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960 |
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Lugar del congreso
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San Sebastian (Spain) |
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Revisores
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Si |
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ISBN o ISSN
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3-540-73006-0 |
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DOI
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Fecha inicio congreso
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20/06/2007 |
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Fecha fin congreso
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22/06/2007 |
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Título de las actas
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