Informatics and Applications
2025, Volume 19, Issue 4, pp 72-77
INDIRECT PROPERTIES IN CLASSIFICATION OF LARGE DATA WITH THE HELP OF CAUSE-AND-EFFECT RELATIONSHIPS
- A. A. Grusho
- N. A. Grusho
- M. I. Zabezhailo
- V. V. Kulchenkov
- E. E. Timonina
Abstract
The usage of cause-and-effect relationships to classify small data sets of high dimension can generate conflicts due to the fact that a significant part of the data does not play a significant role in the classification task and can be considered as random data. In this case, in terms of cause-and-effect relationships, random data can generate pieces ofinformation that interfere with correct classification or generate classification errors. Additional information is needed to neutralize characteristics errors. In the present paper, such additional information was also found using causal relationships. The authors define indirect characteristics that can be used to resolve conflicts and to refine the classification. Using the task ofclassifying ofthree informative classes as an example, it is shown how to obtain and how to use indirect characteristics to resolve conflict situations during the classification process and error prevention process.
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[+] About this article
Title
INDIRECT PROPERTIES IN CLASSIFICATION OF LARGE DATA WITH THE HELP OF CAUSE-AND-EFFECT RELATIONSHIPS
Journal
Informatics and Applications
2025, Volume 19, Issue 4, pp 72-77
Cover Date
2025-30-12
DOI
10.14357/19922264250408
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
classification; cause-and-effect relationships; indirect characteristics of correct classification
Authors
A. A. Grusho  , N. A. Grusho , M. I. Zabezhailo , V. V. Kulchenkov  , and E. E. Timonina
Author Affiliations
Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
VTB Bank, 43-1 Vorontsovskaya Str., Moscow 109147, Russian Federation
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