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Journal of Siberian Federal University. Mathematics & Physics, 2016, Volume 9, Issue 4, Pages 473–480
DOI: https://doi.org/10.17516/1997-1397-2016-9-4-473-480 (Mi jsfu509) 		 
This article is cited in 1 scientific paper (total in 1 paper)

Selecting informative variables in the identification problem

Eugene D. Mihov, Oleg V. Nepomnyashchiy

Institute of Space and Information Technology, Siberian Federal University, Kirensky, 26, Krasnoyarsk, 660074, Russia
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DOI: https://doi.org/10.17516/1997-1397-2016-9-4-473-480
Abstract: The problem of multidimensional object classification with small training sample is considered. The following algorithms of estimating variable informativeness are considered: Ad, Del, AdDel.
A new algorithm for selecting informative variables is proposed. It is based on the optimization of the coefficient vector of the kernel fuzziness. Some modification of this algorithm is also discussed.
The comparative analysis of existing methods for selecting informative variables is presented.
Keywords: classification, small training sample, informative variable, optimization of the coefficient vector of the kernel fuzziness.
Funding agency Grant number
Russian Science Foundation 16-19-10089
The study was performed by a grant from the Russian Science Foundation (project no. 16-19-10089).
Received: 23.06.2016
Received in revised form: 14.08.2016
Accepted: 14.09.2016
Bibliographic databases:
Document Type: Article
UDC: 519.87
Language: English
Citation: Eugene D. Mihov, Oleg V. Nepomnyashchiy, “Selecting informative variables in the identification problem”, J. Sib. Fed. Univ. Math. Phys., 9:4 (2016), 473–480
Citation in format AMSBIB
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\paper Selecting informative variables in the identification problem
\jour J. Sib. Fed. Univ. Math. Phys.
\yr 2016
\vol 9
\issue 4
\pages 473--480
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\crossref{https://doi.org/10.17516/1997-1397-2016-9-4-473-480}
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    • This publication is cited in the following 1 articles:
    1. Kseniya Nazarova, 2024 Conference of Young Researchers in Electrical and Electronic Engineering (ElCon), 2024, 723  crossref
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Журнал Сибирского федерального университета. Серия "Математика и физика"
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    Full-text PDF :74
    References:43
     
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