Analyzing Supersaturated Designs by means of an Information Based Criterion
Résumé
In this paper, we propose a method for analyzing data using a correlation-based measure, named as symmetrical uncertainty. This method combines measures from the information theory field and is used as the main idea of variable selection algorithms developed in data mining. In this work, the symmetrical uncertainty is used from another viewpoint in order to determine more directly the important factors.We evaluate our method by using some of the existing supersaturated designs, obtained according to methods proposed by Tang and Wu \cite{Tang1997} as well as by Koukouvinos et al. \cite{Simos2008}.
Domaines
Calcul [stat.CO]
Origine : Fichiers produits par l'(les) auteur(s)
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