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Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes

The article considers procedures for the formation of sets of informative features, the selection of which is carried out according to pairs of disjoint classes of objects with the algorithm of a hierarchical agglomerative grouping of initial features. The class indices are considered to belong to t...

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Detalles Bibliográficos
Autores principales: Ignatev, N. A., Rahimova, M. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pleiades Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008188/
http://dx.doi.org/10.3103/S0147688222060053
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author Ignatev, N. A.
Rahimova, M. A.
author_facet Ignatev, N. A.
Rahimova, M. A.
author_sort Ignatev, N. A.
collection PubMed
description The article considers procedures for the formation of sets of informative features, the selection of which is carried out according to pairs of disjoint classes of objects with the algorithm of a hierarchical agglomerative grouping of initial features. The class indices are considered to belong to the set of the admissible values of the classification attribute in the original scale. The calculation of latent indicators by groups is used to reduce the dimensionality of space in the description of objects. A measure of the compactness of classes by the latent indicator is proposed, which makes it possible to evaluate sets of features. The set of features that has the maximum value of the compactness measure is selected as informative. The properties of binary relations between classes with respect to the values of the compactness measure are investigated.
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spelling pubmed-100081882023-03-13 Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes Ignatev, N. A. Rahimova, M. A. Sci. Tech. Inf. Proc. Article The article considers procedures for the formation of sets of informative features, the selection of which is carried out according to pairs of disjoint classes of objects with the algorithm of a hierarchical agglomerative grouping of initial features. The class indices are considered to belong to the set of the admissible values of the classification attribute in the original scale. The calculation of latent indicators by groups is used to reduce the dimensionality of space in the description of objects. A measure of the compactness of classes by the latent indicator is proposed, which makes it possible to evaluate sets of features. The set of features that has the maximum value of the compactness measure is selected as informative. The properties of binary relations between classes with respect to the values of the compactness measure are investigated. Pleiades Publishing 2023-03-12 2022 /pmc/articles/PMC10008188/ http://dx.doi.org/10.3103/S0147688222060053 Text en © Allerton Press, Inc. 2022, ISSN 0147-6882, Scientific and Technical Information Processing, 2022, Vol. 49, No. 6, pp. 439–445. © Allerton Press, Inc., 2022.Russian Text © The Author(s), 2021, published in Iskusstvennyi Intellekt i Prinyatie Reshenii, 2021, No. 4, pp. 18–26. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Ignatev, N. A.
Rahimova, M. A.
Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes
title Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes
title_full Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes
title_fullStr Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes
title_full_unstemmed Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes
title_short Formation and Analysis of Sets of Informative Features of Objects by Pairs of Classes
title_sort formation and analysis of sets of informative features of objects by pairs of classes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008188/
http://dx.doi.org/10.3103/S0147688222060053
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