Author(s)

Soroor Behbahani, Ali Moti Nasrabadiv

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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.

SOM Neural Network; Feature; Clustering; Animal

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.