Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications

Murphy, T.B., Dean, N. and Raftery, A.E. (2010) Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications. Annals of Applied Statistics, 4(1), pp. 396-421. (doi:10.1214/09-AOAS279)

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Abstract

Food authenticity studies are concerned with determining if food samples have been correctly labelled or not. Discriminant analysis methods are an integral part of the methodology for food authentication. Motivated by food authenticity applications, a model-based discriminant analysis method that includes variable selection is presented. The discriminant analysis model is fitted in a semi-supervised manner using both labeled and unlabeled data. The method is shown to give excellent classification performance on several high-dimensional multiclass food authenticity datasets with more variables than observations. The variables selected by the proposed method provide information about which variables are meaningful for classification purposes. A headlong search strategy for variable selection is shown to be efficient in terms of computation and achieves excellent classification performance. In applications to several food authenticity datasets, our proposed method outperformed default implementations of Random Forests, AdaBoost, transductive SVMs and Bayesian Multinomial Regression by substantial margins.

Item Type:Articles (Other)
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Dean, Dr Nema
Authors: Murphy, T.B., Dean, N., and Raftery, A.E.
Subjects:H Social Sciences > HA Statistics
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Annals of Applied Statistics
Publisher:Institute of Mathematical Statistics
ISSN:1932-6157
ISSN (Online):1941-7330
Copyright Holders:Copyright © Institute of Mathematical Statistics 2010
First Published:First published in Annals of Applied Statistics 4 (1) : 396-421
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher.

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