Automatic K-Expectation-Maximization (K-EM) clustering algorithm for data mining applications
<p>A non-parametric data clustering technique for achieving efficient data-clustering and improving the number of clusters is presented in this thesis. <I>K</I>-Means and Expectation-Maximization algorithms have been widely deployed in data-clustering applications. Result findings...
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| Format: | Others |
| Language: | en |
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MSSTATE
2016
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| Online Access: | http://sun.library.msstate.edu/ETD-db/theses/available/etd-06292016-160552/ |