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Communication Dans Un Congrès Année : 2013

Model choice for binned-EM algorithms of fourteen parsimonious Gaussian mixture models by BIC and ICL criteria

Hani Hamdan

Résumé

Choosing the right model is an important step in model-based clustering approaches. In this framework, BIC and ICL criteria were proposed to choose a model for clustering of standard data. On the other hand, in order to accelerate the data processing when using EM algorithm, this algorithm was adapted to binned data (binned-EM algorithm). Then fourteen binned-EM algorithms of fourteen parsimonious Gaussian mixture models were developed to replace the binned-EM algorithm of the most general Gaussian mixture model when data have a simple structure. So this paper studies the application of BIC and ICL criteria to select a good model which better fits binned data, when clustering is based on these fourteen binned-EM algorithms. Numerical experiments on simulated and real data are performed, and the experimental results are analyzed.
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Dates et versions

hal-00865793 , version 1 (25-09-2013)

Identifiants

Citer

Jingwen Wu, Hani Hamdan. Model choice for binned-EM algorithms of fourteen parsimonious Gaussian mixture models by BIC and ICL criteria. 2013 International Conference on System Science and Engineering (ICSSE 2013) , Jul 2013, Budapest, Hungary. pp.351-356, ⟨10.1109/ICSSE.2013.6614690⟩. ⟨hal-00865793⟩
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