Summary
A rough self-organizing map (RSOM) with fuzzy discretization of feature space is described here. Discernibility reducts obtained using rough set theory are used to extract domain knowledge in an unsupervised framework. Reducts are then used to determine the initial weights of the network, which are further refined using competitive learning. The superiority of this network in terms of the quality of clusters, learning time, and representation of data is demonstrated quantitatively through experiments across the conventional SOM.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer, Dordrecht, 1991.
A. Skowron, C. Rauszer. The discernibility matrices and functions in information systems. In R. Slowifiski, editor, Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory, 331–363, Kluwer, Dordrecht, 1992.
S.K. Pal, W. Pedrycz, A. Skowron, R. Swiniarski, editors. Rough-neurocomputing (special issue). Vol. 36 of Neurocomputing: An International Journal, 2001.
M. Banerjee, S. Mitra, S.K. Pal. Rough fuzzy MLP: Knowledge encoding and classification. IEEE Transactions on Neural Networks, 9: 1203–1216, 1998.
T. Kohonen. Self-Organizing Maps. Springer, Heidelberg, 2001.
S.K. Pal, S. Mitra. Multi-layer perceptron, fuzzy sets and classification. IEEE Transactions on Neural Networks, 3: 683–697, 1992.
S.K. Pal, S. Mitra. Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing. Wiley, New York, 1999.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Pal, S.K., Dasgupta, B., Mitra, P. (2004). Rough-SOM with Fuzzy Discretization. In: Pal, S.K., Polkowski, L., Skowron, A. (eds) Rough-Neural Computing. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18859-6_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-18859-6_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-62328-8
Online ISBN: 978-3-642-18859-6
eBook Packages: Springer Book Archive