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Titlebook: Large-Scale Parallel Data Mining; Mohammed J. Zaki,Ching-Tien Ho Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 2000 classi

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Parallel Generalized Association Rule Mining on Large Scale PC Clusterorithms and candidate duplication based load balancing strategies for mining generalized association rules and showed our algorithms could attain good performance on 16 nodes parallel computer system. However, as the number of nodes increase, it would be difficult to achieve flat workload distributi
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Parallel Predictor Generationem to predict the properties of new data. For a wide range of techniques, combining predictors built on samples from the training dataset provides lower error rates, faster construction, or both, than a predictor built from the entire training dataset. This provides a natural parallelization strateg
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Collective, Hierarchical Clustering from Distributed, Heterogeneous Dataes local cluster models and then combines them to generate the global cluster model of the data. The proposed algorithm runs in .(|.|..) time, with a .(|.|.) space requirement and .(.) communication requirement, where . is the number of elements in the data set and . is the number of data sites. Thi
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naher Zukunft zweifellos eine Beschleunigung erfährt (vgl. Geißler/Meyer 1996: 336).. Dennoch sei darauf hingewiesen, dass es zwischen empirisch feststellbaren demografischen Veränderungen und deren öffentlicher Wahrnehmung zu unterscheiden gilt. Für die sozialwissenschaftliche Theorie und Empirie i
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