Facilitating Fuzzy Association Rules Mining by Using Multi-Objective Genetic Algorithms for Automated Clustering

Authors:
Mehmet Kaya;Reda Alhajj
Affiliations:
-;-
Venue:
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Year:
2003

Citing 11
Cited 9

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Abstract

In this paper, we propose an automated clustering methodbased on multi-objective genetic algorithms (GA); the aim ofthis method is to automatically cluster values of a givenquantitative attribute to obtain large number of largeitemsets in low duration (time). We compare the proposedmulti-objective GA-based approach with CURE-basedapproach. In addition to the autonomous specification offuzzy sets, experimental results showed that the proposedautomated clustering exhibits good performance overCURE-based approach in terms of runtime as well as thenumber of large itemsets and interesting association rules.