Distributed unsupervised learning using the multisoft machine
Information Sciences—Informatics and Computer Science: An International Journal
Image-mapped data clustering: An efficient technique for clustering large data sets
Intelligent Data Analysis
Survey of Clustering: Algorithms and Applications
International Journal of Information Retrieval Research
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Genetic algorithms (GA) are useful in solving complex optimization problems. By posing pattern clustering as an optimization problem, GAs can be used to obtain optimal minimum squared error partitions. In order to improve the total execution time, a distributed algorithm has been developed using the divide and conquer approach. Using a standard communication library called PVM, the distributed algorithm has been implemented on a workstation cluster: the GA approach gives better quality clusters for many data sets compared to a standard K-means clustering algorithm. We have achieved a near linear speedup for the distributed implementation.