Mohebi, Ehsan and Sap, M. N. N. (2009) Rough set based clustering of the self organizing map. In: Proceedings - 2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009. Institute of Electrical and Electronics Engineers, New York, 82 -85. ISBN 978-076953580-7
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Official URL: http://dx.doi.org/10.1109/ACIIDS.2009.79
The Kohonen Self Organizing Map (SOM) is an excellent tool in exploratory phase of data mining. The SOM is a popular tool that maps a high-dimensional space onto a small number of dimensions by placing similar elements close together, forming clusters. When the number of SOM units is large, to facilitate quantitative analysis of the map and the data, similar units needs to be grouped i.e., clustered. In this paper a two-level clustering based on SOM is proposed, which employs rough set theory to capture the inherent uncertainty involved in cluster analysis. The two-stage procedure (first using SOM to produce the prototypes that are then clustered in the second stage) is found to perform well when compared with crisp clustering of the data and increase the accuracy.
|Item Type:||Book Section|
|Additional Information:||2009 1st Asian Conference on Intelligent Information and Database Systems, ACIIDS 2009; Dong Hoi; 1 April 2009 through 3 April 2009|
|Uncontrolled Keywords:||clustering, overlapped data, rough set, SOM, uncertainty|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System|
|Deposited By:||Liza Porijo|
|Deposited On:||18 Jul 2011 08:01|
|Last Modified:||18 Jul 2011 08:01|
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