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Some Estimates of Computational Complexity When Predicting the Properties of New Objects Using Characteristic Functions

Some Estimates of Computational Complexity When Predicting the Properties of New Objects Using... —This paper discusses approaches to evaluating the quality of intelligent data analysis results in diagnostic tasks. The reliability (indisputability) of empirical dependencies established during training (interpolation–extrapolation) on precedents is evaluated using a special mathematical tool, that is, characteristic functions. Characteristic functions are generated on the available sample of empirical data based on similarity analysis of precedent descriptions, formalized as a binary algebraic operation. Some estimates of the computational complexity of applying the proposed mathematical technique of characteristic functions to predicting (diagnosing) the properties of newly studied precedents are presented. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Automatic Documentation and Mathematical Linguistics Springer Journals

Some Estimates of Computational Complexity When Predicting the Properties of New Objects Using Characteristic Functions

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References (9)

Publisher
Springer Journals
Copyright
Copyright © Allerton Press, Inc. 2020. ISSN 0005-1055, Automatic Documentation and Mathematical Linguistics, 2020, Vol. 54, No. 6, pp. 298–305. © Allerton Press, Inc., 2020. Russian Text © The Author(s), 2020, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2: Informatsionnye Protsessy i Sistemy, 2020, No. 12, pp. 1–8.
ISSN
0005-1055
eISSN
1934-8371
DOI
10.3103/S0005105520060072
Publisher site
See Article on Publisher Site

Abstract

—This paper discusses approaches to evaluating the quality of intelligent data analysis results in diagnostic tasks. The reliability (indisputability) of empirical dependencies established during training (interpolation–extrapolation) on precedents is evaluated using a special mathematical tool, that is, characteristic functions. Characteristic functions are generated on the available sample of empirical data based on similarity analysis of precedent descriptions, formalized as a binary algebraic operation. Some estimates of the computational complexity of applying the proposed mathematical technique of characteristic functions to predicting (diagnosing) the properties of newly studied precedents are presented.

Journal

Automatic Documentation and Mathematical LinguisticsSpringer Journals

Published: Feb 26, 2021

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