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Интеллектуальная Система Тематического Исследования НАукометрических данных |
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Supervised Classification Problem: New Models of Logical Correctorsстатья
Информация о цитировании статьи получена из
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 23 января 2026 г.
- Авторы: Genrikhova I.E., Djukova E.V.
- Журнал: Journal of Computer and Systems Sciences International
- Том: 64
- Номер: 1
- Год издания: 2025
- Издательство: Maik Nauka/Interperiodica Publishing
- Местоположение издательства: Russian Federation
- Первая страница: 36
- Последняя страница: 45
- DOI: 10.1134/S1064230725700030
- Аннотация: An approach to the correct supervised classification problem based on the application oflogical data analysis methods is considered. The operation scheme of logical classifier models aimedat constructing special fragments of precedent descriptions, called correct elementary classifiers, is described. More complex models, namely, models of logical correctors, are based on the synthesis of families of the correct sets of elementary classifiers. Unlike classical models, logical correctors show good results in the case of multivalued features, i.e., features with a large number of different values. The article examines issues related to reducing time costs and improving the quality of classification of logical correctors. New deterministic and stochastic variants of such models are proposed, designedto work with partially ordered data. The results of experiments on model and real data are presented.
- Добавил в систему: Дюкова Елена Всеволодовна