Application of SOM neural network in clustering ()
Abstract
The Self-Organizing Map (SOM) is an unsupervised neural network algorithm that projects high-dimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map. One of the SOM neural network’s applications is clustering of animals due their features. In this paper we produce an experiment to analyze the SOM in clustering different species of animals.
Share and Cite:
Behbahani, S. and Nasrabadiv, A. (2009) Application of SOM neural network in clustering.
Journal of Biomedical Science and Engineering,
2, 637-643. doi:
10.4236/jbise.2009.28093.
Conflicts of Interest
The authors declare no conflicts of interest.
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