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Regression analysis / Model selection / Statistical classification / Linear discriminant analysis / Bayesian information criterion / Feature selection / Discriminant / Principal component analysis / Random forest / Statistics / Multivariate statistics / Econometrics


Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications
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Document Date: 2010-06-07 17:10:14


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City

Pork / /

Company

N. DEAN AND A. E. / Dg Ag / /

Country

Turkey / Greece / /

Facility

University of Washington / University College Dublin / University of Glasgow / Institute of Mathematical Statistics / /

IndustryTerm

olive oil data / Search strategies / virgin olive oil samples / food sample / olive oil samples / food science applications / Food producers / food authenticity applications / food samples / chemical and technological aspects / gas chromatography / image processing / food science / food description / Food authenticity studies / ultraviolet spectroscopic technology / headlong search / high-dimensional multiclass food authenticity data sets / statistical applications / food products / food authenticity data sets / authentic food / headlong search strategy / food authenticity study / food authenticity / food authentication / chemical bonds / /

NaturalFeature

Random Forests / /

Organization

University of Washington / National Institute of Health / National Science Foundation / Institute of Mathematical Statistics / University College Dublin / Science Foundation of Ireland Basic Research Grant / University of Glasgow / /

Person

Mk / /

Position

Grouping model for model comparison purposes / model / mixture model for the unlabeled data / representative / Dean / /

Technology

proteomics / spectroscopy / ATM / gas chromatography / using ultraviolet spectroscopic technology / machine learning / image processing / /

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