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Mining Comprehensive Clustering Rules with an Evolutionary Algorithm  (Make Corrections)  
Ioannis Sara, Phil Trinder, and Ali Zalzala School of Mathematics and...



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Abstract: In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. (Update)

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BibTeX entry:   (Update)

@misc{ phil-mining,
  author = "Ioannis Sara Phil",
  title = "Mining Comprehensive Clustering Rules with an Evolutionary Algorithm",
  url = "citeseer.ist.psu.edu/630141.html" }
Citations (may not include all citations):
2138   Genetic Algorithms in Search (context) - Goldberg - 1989
805   Algorithms for Clustering Data (context) - Jain, Dubes - 1988
475   Automatic subspace clustering of high dimensional data for d.. - Agrawal, Gehrke et al. - 1998
225   Data Mining: Concepts and Techniques (context) - Han, Kamber - 2000
206   Genetic Algorithms + Data Structures = Evolution Programs (context) - Michalewicz - 1996
149   Multivariate Density Estimation (context) - Scott - 1992
50   BIRCH: an ecient data clustering method for very large datab.. (context) - Zhang, Ramakrishnan et al.
30   CURE: An ecient clustering algorithm for large databases (context) - Guha, Rastogi et al. - 1998
24   Chameleon: Hierarchical clustering using dynamic modeling (context) - Karypis, Han et al. - 1999
22   Clustering with a genetically optimized approach - Hall, Ozyurt et al. - 1999
8   An ecient approach to clustering in large multimedia databas.. (context) - Hinneburg, Keim - 1998
2   A genetic rule-based data clustering toolkit - Sara, Zalzala et al. - 2002

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