Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia
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Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia, 2020, Volume 490, Pages 67–70
DOI: https://doi.org/10.31857/S2686954320010129 (Mi danma36) 		 
INFORMATICS

Completeness criteria for a linear model of classification algorithms with respect to families of decision rules

A. G. Dyakonova, A. M. Golovinab

a Lomonosov Moscow State University, Moscow, Russian Federation
b Bauman Moscow State Technical University, Moscow, Russian Federation
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DOI: https://doi.org/10.31857/S2686954320010129
Abstract: In the framework of Zhuravlev’s algebraic approach to classification problems, a linear model of algorithms is investigated (estimates of class membership are generated by linear regressions). The possibility of weakening the completeness requirement (obtaining an arbitrary estimation matrix) in order to obtain any classification of a fixed set of objects by using special decision rules is investigated.
Keywords: classification, linear algorithms, algebraic approach, correctness, completeness.
Funding agency Grant number
NTI 13/1251/2018
This research was performed at the Center for Big Data Storage and Analysis of Lomonosov Moscow State University and was supported by the National Technology Initiative Foundation (13/1251/2018 of December 11, 2018).
Presented: K. V. Rudakov
Received: 29.11.2019
Revised: 29.11.2019
Accepted: 29.11.2019
English version:
Doklady Mathematics, 2020, Volume 101, Issue 1, Pages 57–59
DOI: https://doi.org/10.1134/S1064562420010123
Bibliographic databases:
Document Type: Article
UDC: 519.7
Language: Russian
Citation: A. G. Dyakonov, A. M. Golovina, “Completeness criteria for a linear model of classification algorithms with respect to families of decision rules”, Dokl. RAN. Math. Inf. Proc. Upr., 490 (2020), 67–70; Dokl. Math., 101:1 (2020), 57–59
Citation in format AMSBIB
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\by A.~G.~Dyakonov, A.~M.~Golovina
\paper Completeness criteria for a linear model of classification algorithms with respect to families of decision rules
\jour Dokl. RAN. Math. Inf. Proc. Upr.
\yr 2020
\vol 490
\pages 67--70
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\crossref{https://doi.org/10.31857/S2686954320010129}
\zmath{https://zbmath.org/?q=an:07424552}
\elib{https://elibrary.ru/item.asp?id=42579064}
\transl
\jour Dokl. Math.
\yr 2020
\vol 101
\issue 1
\pages 57--59
\crossref{https://doi.org/10.1134/S1064562420010123}
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