J.T. Potts, Seeking Parallelism in Discovery Programs, Master Thesis, University of Texas at Arlington, 1996. Home/Search Document Not in Database Summary Related Articles Check |
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Scalable Parallel Clustering for Data Mining on.. - Foti, Lipari, Pizzuti.. (2000) (4 citations) (Correct)
....can provide the appropriate setting where to execute clustering algorithms for extracting knowledge from largescale data repositories. Recently there has been an increasing interest in parallel implementations of data clustering algorithms. Parallel approaches to clustering can be found in [8, 4, 9, 5, 10]. In this paper we consider a parallel clustering algorithm based on Bayesian classification for distributed memory multicomputers. We propose a parallel implementation of the AutoClass algorithm, called P AutoClass, and validate by experimental measurements the scalability of our parallelization ....
....code starting from the sequential program to which only few instructions have been added. The first data parallel version of AutoClass has been developed in Lisp to run on a Connection Machine 2 [1] and the second one has been developed adding C code to the C source to run it on a CM 5 [9]. These 1 2 3 4 5 6 7 8 9 10 12345678910 no. of processors speedup [T1 Tp] 5000 tuples 10000 tuples 20000 tuples 30000 tuples 40000 tuples 50000 tuples 100000 tuples linear 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 13510 Number of processors Times per base cycle ....
J.T. Potts. Seeking Parallelism in Discovery Programs. Master Thesis, University of Texas at Arlington, 1996.
Parallel Unsupervised k-Windows: An Efficient.. - Tasoulis.. (2003) (Correct)
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J.T. Potts, Seeking Parallelism in Discovery Programs, Master Thesis, University of Texas at Arlington, 1996.
Parallelizing the Unsupervised k-Windows Clustering.. - Alevizos, Tasoulis.. (Correct)
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J.T. Potts, Seeking Parallelism in Discovery Programs, Master Thesis, University of Texas at Arlington, 1996.
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