The application of k-medoids and PAM to the clustering of rules

A. P. Reynolds, G. Richards, V. J. Rayward-Smith

Research output: Chapter in Book/Report/Conference proceedingChapter

46 Citations (Scopus)

Abstract

Earlier research has resulted in the production of an ‘all-rules’ algorithm for data-mining that produces all conjunctive rules of above given confidence and coverage thresholds. While this is a useful tool, it may produce a large number of rules. This paper describes the application of two clustering algorithms to these rules, in order to identify sets of similar rules and to better understand the data.
Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning – IDEAL 2004
EditorsZheng Rong Yang, Hujun Yin, Richard M. Everson
PublisherSpringer
Pages173-178
Number of pages6
Volume3177
ISBN (Print)978-3-540-22881-3
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science
PublisherSpringer-Verlag

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