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Problemy Fiziki, Matematiki i Tekhniki (Problems of Physics, Mathematics and Technics), 2023, Issue 4(57), Pages 94–102
DOI: https://doi.org/10.54341/20778708_2023_4_57_94
(Mi pfmt942)
 

This article is cited in 1 scientific paper (total in 1 paper)

INFORMATION SCIENCE

Research of the performance of machine learning algorithms in data classification problems

E. V. Timoschenkoa, A. F. Razhkovb

a Mogilev State A. Kuleshov University
b United Institute of Informatics Problems of the National Academy of Sciences of Belarus, Minsk
Full-text PDF (306 kB) Citations (1)
References:
DOI: https://doi.org/10.54341/20778708_2023_4_57_94
Abstract: An approach to solving the problem of constructing machine learning models in solving data classification problems is proposed. Using the example of analyzing biomedical data sets, the performance of machine learning algorithms tuned using pre-optimized hyperparameters is compared. The best values of hyperparameters that provide effective prediction were found for the most common machine learning algorithms.
Keywords: machine learning, data classification, hyperparameter optimization, big data processing, disease prediction.
Received: 29.09.2023
Bibliographic databases:
Document Type: Article
UDC: 004.891.3, 004.855.5, 004.9
Language: Russian
Citation: E. V. Timoschenko, A. F. Razhkov, “Research of the performance of machine learning algorithms in data classification problems”, PFMT, 2023, no. 4(57), 94–102
Citation in format AMSBIB
\Bibitem{TimRaz23}
\by E.~V.~Timoschenko, A.~F.~Razhkov
\paper Research of the performance of machine learning algorithms in data classification problems
\jour PFMT
\yr 2023
\issue 4(57)
\pages 94--102
\mathnet{http://mi.mathnet.ru/pfmt942}
\edn{https://elibrary.ru/ZCJEJY}
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  • https://www.mathnet.ru/eng/pfmt/y2023/i4/p94
  • This publication is cited in the following 1 articles:
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