Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007) 2007
DOI: 10.1109/isda.2007.118
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EDACluster: an Evolutionary Density and Grid-Based Clustering Algorithm

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Cited by 4 publications
(2 citation statements)
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“…An evolutionary algorithm -more precisely, an Estimation of Distribution Algorithm -using a density-based fitness function is described in [31]. In this algorithm, the fitness function is essentially computed as the average density over the clusters represented by an individual, where the density of a cluster is simply the number of objects in the cluster divided by the size of the region defining that cluster.…”
Section: To Appear In Ieee Transactions On Systems Man and Cybernetmentioning
confidence: 99%
“…An evolutionary algorithm -more precisely, an Estimation of Distribution Algorithm -using a density-based fitness function is described in [31]. In this algorithm, the fitness function is essentially computed as the average density over the clusters represented by an individual, where the density of a cluster is simply the number of objects in the cluster divided by the size of the region defining that cluster.…”
Section: To Appear In Ieee Transactions On Systems Man and Cybernetmentioning
confidence: 99%
“…Finally, they use a grid structure for the clustering and they select the data tuples based on their distance to the centroid while DENSE selects the most representative ones. Authors in [114] propose EDACluster that is also based on grids to perform density clustering.…”
Section: Related Workmentioning
confidence: 99%