Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing

The Kohonen self organizing map is widely used as a popular tool in the exploratory phase of data mining. The SOM (Self Organizing Maps) maps high dimensional space into a 2-dimensional grid by placing similar elements close together, forming clusters. Recently research experiments presented that to...

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Main Authors: Mohebi, E., Sap, M. N. M.
Format: Book Section
Published: IEEE 2009
Subjects:
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author Mohebi, E.
Sap, M. N. M.
author_facet Mohebi, E.
Sap, M. N. M.
author_sort Mohebi, E.
collection ePrints
description The Kohonen self organizing map is widely used as a popular tool in the exploratory phase of data mining. The SOM (Self Organizing Maps) maps high dimensional space into a 2-dimensional grid by placing similar elements close together, forming clusters. Recently research experiments presented that to capture the uncertainty involved in cluster analysis, it is not necessary to have crisp boundaries in some clustering operations. In this paper to overcome the uncertainty, an optimized clustering algorithm based on SOM which employs the rough set theory and the Simulated Annealing as a general technique for optimization problems is proposed. The optimized twolevel stage SA-Rough SOM (Simulated Annealing - Rough Self Organizing Map) (first using SOM to produce the prototypes that are then clustered in the second stage based on the combination of rough set and simulated annealing) is found to perform well and more accurate compared with the crisp clustering methods (i.e. Incremental SOM) and reduces the errors.
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spelling utm.eprints-148702011-09-30T15:12:58Z http://eprints.utm.my/14870/ Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing Mohebi, E. Sap, M. N. M. QA75 Electronic computers. Computer science The Kohonen self organizing map is widely used as a popular tool in the exploratory phase of data mining. The SOM (Self Organizing Maps) maps high dimensional space into a 2-dimensional grid by placing similar elements close together, forming clusters. Recently research experiments presented that to capture the uncertainty involved in cluster analysis, it is not necessary to have crisp boundaries in some clustering operations. In this paper to overcome the uncertainty, an optimized clustering algorithm based on SOM which employs the rough set theory and the Simulated Annealing as a general technique for optimization problems is proposed. The optimized twolevel stage SA-Rough SOM (Simulated Annealing - Rough Self Organizing Map) (first using SOM to produce the prototypes that are then clustered in the second stage based on the combination of rough set and simulated annealing) is found to perform well and more accurate compared with the crisp clustering methods (i.e. Incremental SOM) and reduces the errors. IEEE 2009 Book Section PeerReviewed Mohebi, E. and Sap, M. N. M. (2009) Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing. In: 2009 11th International Conference on Computer Modelling and Simulation. Article number 4809737 . IEEE, pp. 53-58. ISBN 978-076953593-7 http://dx.doi.org/10.1109/UKSIM.2009.28 doi:10.1109/UKSIM.2009.28
spellingShingle QA75 Electronic computers. Computer science
Mohebi, E.
Sap, M. N. M.
Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing
title Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing
title_full Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing
title_fullStr Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing
title_full_unstemmed Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing
title_short Hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing
title_sort hybrid kohonen self organizing map for the uncertainty involved in overlapping clusters using simulated annealing
topic QA75 Electronic computers. Computer science
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AT sapmnm hybridkohonenselforganizingmapfortheuncertaintyinvolvedinoverlappingclustersusingsimulatedannealing