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On feature selection, curse-of-dimensionality and error probability in discriminant analysis
Mid Sweden University, Faculty of Science, Technology and Media, Department of Engineering, Physics and Mathematics.
Responsible organisation
2003 (English)In: Journal of statistical planning and inference, ISSN 0378-3758, Vol. 115, no 2, 565-584 p.Article in journal (Refereed) Published
Abstract [en]

Discrimination performance, measured by the limiting error probability, is considered from the point of view of feature discriminating power. For assessing the latter, a concept of feature informativeness is introduced. A threshold feature selection technique is considered. Selection is incorporated into the discriminant function by means of an inclusion-exclusion factor which eliminates the sets of features whose informativeness do not exceed a given threshold. An issue is how this selection procedure affects the error rate when sample based estimates are used in the discriminant function. This effect is evaluated in a growing dimension asymptotic framework. In particular, the increase of the moments of the discriminant function induced by the curse-of-dimensionality is shown together with the effect of the threshold-based feature selection. The asymptotic normality of the discriminant function, which makes it possible to express the overall error probability in a closed form and view it as a function of a given threshold of selection.

Place, publisher, year, edition, pages
2003. Vol. 115, no 2, 565-584 p.
Keyword [en]
Growing dimension asymptotics
National Category
Mathematics
Identifiers
URN: urn:nbn:se:miun:diva-2267DOI: 10.1016/S0378-3758(02)00166-0ISI: 000183378000015Scopus ID: 2-s2.0-0037902234Local ID: 1493OAI: oai:DiVA.org:miun-2267DiVA: diva2:27299
Available from: 2008-09-30 Created: 2008-09-30 Last updated: 2016-10-24Bibliographically approved

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CiteExportLink to record
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