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Sibirskii Zhurnal Industrial'noi Matematiki, 2014, Volume 17, Number 1, Pages 86–98 (Mi sjim822)  

This article is cited in 4 scientific papers (total in 4 papers)

Regression models in the classification problem

V. M. Nedel'ko

Sobolev Institute of Mathematics, 4 Koptyug av., 630090 Novosibirsk
Full-text PDF (397 kB) Citations (4)
References:
Abstract: We carry out a comparative analysis of the efficiency of several methods of classification (pattern recognition) based on regression models, in particular, logistic regression and its modifications. A new method for constructing a decision function is proposed. The method is based on the maximization of the area under the error curve over the linear functions in the space of the decision functions obtained by a special transformation. The performance of the method is illustrated by solving an applied problem.
Keywords: regression analysis, pattern recognition, machine learning, decision function, misclassification probability, logistic regression, Fisher linear discriminant.
Received: 17.10.2013
Bibliographic databases:
Document Type: Article
UDC: 519.246
Language: Russian
Citation: V. M. Nedel'ko, “Regression models in the classification problem”, Sib. Zh. Ind. Mat., 17:1 (2014), 86–98
Citation in format AMSBIB
\Bibitem{Ned14}
\by V.~M.~Nedel'ko
\paper Regression models in the classification problem
\jour Sib. Zh. Ind. Mat.
\yr 2014
\vol 17
\issue 1
\pages 86--98
\mathnet{http://mi.mathnet.ru/sjim822}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=3379257}
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  • https://www.mathnet.ru/eng/sjim/v17/i1/p86
  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Сибирский журнал индустриальной математики
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    Abstract page:747
    Full-text PDF :710
    References:60
    First page:12
     
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