Classification and clustering of granular data

Bargiela, A. and Pedrycz, W., 2001. Classification and clustering of granular data. In: Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference. Piscataway, NJ: Institute of Electrical and Electronic Engineers, pp. 1696-1701. ISBN 0780370783

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Abstract

Information granules are formed to reduce the complexity of the description of real-world systems. The improved generality of information granules is attained through sacrificing some of the numerical precision of point-data. In this study we consider a hyperbox-based clustering and classification of granular data, and discuss detailed criteria for the assessment of the quality of the combined classification and clustering. The robustness of the criteria is assessed on both synthetic data and real-life data from the domain of traffic control

Item Type: Chapter in book
Creators: Bargiela, A. and Pedrycz, W.
Publisher: Institute of Electrical and Electronic Engineers
Place of Publication: Piscataway, NJ
Date: 2001
Volume: 3
Divisions: Schools > School of Science and Technology
Depositing User: EPrints Services
Date Added: 09 Oct 2015 11:06
Last Modified: 19 Oct 2015 14:41
URI: http://irep.ntu.ac.uk/id/eprint/22865

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