Clustering rules: A comparison of partitioning and hierarchical clustering algorithms

Reynolds, A. P., Richards, G., de la Iglesia, B. ORCID: https://orcid.org/0000-0003-2675-5826 and Rayward-Smith, V. J. (2006) Clustering rules: A comparison of partitioning and hierarchical clustering algorithms. Journal of Mathematical Modelling and Algorithms, 5 (4). pp. 475-504. ISSN 1570-1166

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Abstract

Previous research has resulted in a number of different algorithms for rule discovery. Two approaches discussed here, the ‘all-rules’ algorithm and multi-objective metaheuristics, both result in the production of a large number of partial classification rules, or ‘nuggets’, for describing different subsets of the records in the class of interest. This paper describes the application of a number of different clustering algorithms to these rules, in order to identify similar rules and to better understand the data.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Medicine and Health Sciences > Research Centres > Business and Local Government Data Research Centre (former - to 2023)
Faculty of Science > Research Groups > Data Science and Statistics
Faculty of Science > Research Groups > Norwich Epidemiology Centre
Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
Depositing User: Vishal Gautam
Date Deposited: 26 May 2011 10:40
Last Modified: 17 Apr 2023 23:35
URI: https://ueaeprints.uea.ac.uk/id/eprint/22070
DOI: 10.1007/s10852-005-9022-1

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