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README.md

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+# MEteorit
+Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributions
+
+MEteoritS is a toolbox containg several original and flexible mixtures-of-experts models to model, cluster and classify heteregenous data in many complex situations where the data are distributed according non-normal, possibly skewed distributions, and when they might be corrupted by atypical observations. The toolbox contains in particular sparse mixture-of-experts models for high-dimensional data. 
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+Our (dis-)covered meteorites are for instance the following:
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+NMoE
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+NNMoE
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+tMoE
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+StMoE
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+.
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+RMoE
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+The models and algorithms are developped and written in Matlab by Faicel Chamroukhi, and translated and designed into R packages by Florian Lecocq, Marius Bartcus and Faicel Chamroukhi.
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+#References
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+Hien D. Nguyen and Faicel Chamroukhi. Practical and theoretical aspects of mixture-of-experts modeling: An overview. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery Wiley Periodicals, Inc., pages:e1246–n/a, Feb., 2018
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+F. Chamroukhi. Skew $t$ mixture of experts. Neurocomputing - Elsevier, Vol. 266, pages:390-408, November, 2017 
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+F. Chamroukhi. Robust mixture of experts modeling using the $t$-distribution. Neural Networks - Elsevier, Vol. 79, pages:20–36, 2016
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+F. Chamroukhi. Skew-Normal Mixture of Experts., July, 2016, The International Joint Conference on Neural Networks (IEEE IJCNN).
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+Chamroukhi, F. Statistical learning of latent data models for complex data analysis. Habilitation Thesis (HDR), Université de Toulon, 07 december, 2015 
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+Chamroukhi, F.. Hidden process regression for curve modeling, classification and tracking. Ph.D. Thesis, Université de Technologie de Compiègne, 13 december, 2010
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+Chamroukhi, F., Samé, A., Govaert, G. and Aknin, P.. Time series modeling by a regression approach based on a latent process. Neural Networks Elsevier Science Ltd.., Vol. 22(5-6), pages:593–602, 2009