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Abstract Details
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Activity Number:
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118
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 1, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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| Abstract - #302389 |
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Title:
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A New Initialization Procedure for the EM Algorithm in Gaussian Mixture Models
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Author(s):
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Volodymyr Melnykov*+ and Igor Melnykov
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Companies:
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North Dakota State University and Colorado State University at Pueblo
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Address:
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Department of Statistics, Fargo, ND, 58108-6050, USA
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Keywords:
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EM algorithm ;
Gaussian mixture model ;
initialization
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Abstract:
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The success of convergence of the EM algorithm in finite mixture models depends on effective initialization. There are multiple approaches proposed in literature that deal with this problem. However, there is no method that can be preferred over the others in all cases. We propose a new procedure for Gaussian mixtures that can be seen as a generalization of popular emEM and Rnd-EM algorithms. The suggested method demonstrates promising performance and good results in many cases. We illustrate the proposed approach on several simulated and classification datasets.
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