Clustering rules: A comparison of partitioning and hierarchical clustering algorithms

A. P. Reynolds, G. Richards, B. de la Iglesia, V. J. Rayward-Smith

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391 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)475-504
Number of pages30
JournalJournal of Mathematical Modelling and Algorithms
Issue number4
Publication statusPublished - 2006

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