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Preprints of the Keldysh Institute of Applied Mathematics, 2018, 255, 40 pp.
DOI: https://doi.org/10.20948/prepr-2018-255
(Mi ipmp2612)
 

This article is cited in 9 scientific papers (total in 9 papers)

The structure of the training base of the statistical classifier of the states of the human body systems

B. M. Gavrikov, M. B. Gavrikov, N. V. Pestryakova, R. V. Stavitskii
References:
Abstract: The properties of the classifier based on the polynomial regression method used to assess human health according to peripheral blood data are investigated. The structure of the training base of seven body systems for men and nine for women was analyzed. For each of the four health classes, the features of the mutual disposition of their elements are considered, their pairs are alien, as well as their own and alien elements relative to the center of mass. The relationship between the adequate complexity of the classifier and the structure of the training set is shown.
Keywords: human health, body system, peripheral blood, classification, polynomial regression.
Funding agency Grant number
Russian Foundation for Basic Research 16-07-00742_а
Bibliographic databases:
Document Type: Preprint
Language: Russian
Citation: B. M. Gavrikov, M. B. Gavrikov, N. V. Pestryakova, R. V. Stavitskii, “The structure of the training base of the statistical classifier of the states of the human body systems”, Keldysh Institute preprints, 2018, 255, 40 pp.
Citation in format AMSBIB
\Bibitem{GavGavPes18}
\by B.~M.~Gavrikov, M.~B.~Gavrikov, N.~V.~Pestryakova, R.~V.~Stavitskii
\paper The structure of the training base of the statistical classifier of the states of the human body systems
\jour Keldysh Institute preprints
\yr 2018
\papernumber 255
\totalpages 40
\mathnet{http://mi.mathnet.ru/ipmp2612}
\crossref{https://doi.org/10.20948/prepr-2018-255}
\elib{https://elibrary.ru/item.asp?id=36533060}
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  • https://www.mathnet.ru/eng/ipmp2612
  • https://www.mathnet.ru/eng/ipmp/y2018/p255
  • This publication is cited in the following 9 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Препринты Института прикладной математики им. М. В. Келдыша РАН
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    Full-text PDF :27
    References:32
     
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