KFU. Card publication. Analysis of Relationships Between Co-Symmetric Dissimilarity Measures of Probability Distributions with Involutive Negations

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ANALYSIS OF RELATIONSHIPS BETWEEN CO-SYMMETRIC DISSIMILARITY MEASURES OF PROBABILITY DISTRIBUTIONS WITH INVOLUTIVE NEGATIONS

Form of presentation

Articles in international journals and collections

Year of publication

2024

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Authors, employees of KFU

Batyrshin Ildar Zakirzyanovich, author

Kubysheva Nailya Iskhakovna, author

Other authors

Ensastegui-Ortega Maria Elena , author

Gelbukh Alexander , author

Bibliographic description in the original language

Ensastegui-Ortega, M. E., Batyrshin, I., Gelbukh, A., & Kubysheva, N. (2024). Analysis of Relationships Between Co-Symmetric Dissimilarity Measures of Probability Distributions with Involutive Negations. Computación y Sistemas, 28(2).

Annotation

Abstract. Learning from data in almost any human activity is a very important task, usually using similarity or dissimilarity between data. Recently, it was shown the importance of considering the involution operation defined on the data domain which reflects a symmetry of data structures. This symmetry should be taken into account in data analysis. Co-symmetric similarity and dissimilarity measures defined over a set with involution play an important role in data analysis. In this paper, four dissimilarity functions over the set of probability distributions are created that meet the property of cosymmetry with respect to the involutive negation of distributions. Scatter graphs are generated from their respective dissimilarity matrices to compare the similarity between them. Additionally, the Pearson, Kendall, and Spearman correlation coefficients are calculated to numerically assess the relationship that exists. Subsequently, four dissimilarity functions are considered due to their higher correlation with those studied in this paper. They are divided into two groups, and an analysis is conducted to determine which are more correlated.

Keywords

Co-symmetry, correlation, dissimilarity, involution, probability distribution.

The name of the journal

Computación y Sistemas

URL

https://cys.cic.ipn.mx/ojs/index.php/CyS/article/view/5049/3712

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=303035&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Batyrshin Ildar Zakirzyanovich	ru_RU
dc.contributor.author	Kubysheva Nailya Iskhakovna	ru_RU
dc.contributor.author	Ensastegui-Ortega Maria Elena	ru_RU
dc.contributor.author	Gelbukh Alexander	ru_RU
dc.date.accessioned	2024-01-01T00:00:00Z	ru_RU
dc.date.available	2024-01-01T00:00:00Z	ru_RU
dc.date.issued	2024	ru_RU
dc.identifier.citation	Ensastegui-Ortega, M. E., Batyrshin, I., Gelbukh, A., & Kubysheva, N. (2024). Analysis of Relationships Between Co-Symmetric Dissimilarity Measures of Probability Distributions with Involutive Negations. Computación y Sistemas, 28(2).	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=303035&p_lang=2	ru_RU
dc.description.abstract	Computación y Sistemas	ru_RU
dc.description.abstract	Abstract. Learning from data in almost any human activity is a very important task, usually using similarity or dissimilarity between data. Recently, it was shown the importance of considering the involution operation defined on the data domain which reflects a symmetry of data structures. This symmetry should be taken into account in data analysis. Co-symmetric similarity and dissimilarity measures defined over a set with involution play an important role in data analysis. In this paper, four dissimilarity functions over the set of probability distributions are created that meet the property of cosymmetry with respect to the involutive negation of distributions. Scatter graphs are generated from their respective dissimilarity matrices to compare the similarity between them. Additionally, the Pearson, Kendall, and Spearman correlation coefficients are calculated to numerically assess the relationship that exists. Subsequently, four dissimilarity functions are considered due to their higher correlation with those studied in this paper. They are divided into two groups, and an analysis is conducted to determine which are more correlated.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Co-symmetry	ru_RU
dc.subject	correlation	ru_RU
dc.subject	dissimilarity	ru_RU
dc.subject	involution	ru_RU
dc.subject	probability distribution.	ru_RU
dc.title	Analysis of Relationships Between Co-Symmetric Dissimilarity Measures of Probability Distributions with Involutive Negations	ru_RU
dc.type	Articles in international journals and collections	ru_RU