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UMBC High Performance Computing Facility
Please note that this page is under construction. We are documenting the 240-node cluster maya that will be available in Spring 2014. Currently, the cluster tara is still available. Please see the 2013 Resources Pages under the Resources tab.
Distributed Principal Direction Divisive Partitioning
Jacob Kogan, Department of Mathematics and Statistics

Clustering is used in a number of traditionally distant fields to describe methods for grouping of unlabeled data. Clustering very large datasets is a contemporary data mining challenge. This project concerns an application of Principal Direction Divisive Partitioning clustering algorithm (PDDP) introduced by D. Boley to a dataset residing in a number of computers connected in a network. Performance of PDDP and Distributed PDDP for datasets of moderate size will be compared.