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A Method for Improving the Accuracy of Regression Models Based on Ordinal-Invariant Pattern Clustering
Procedia Computer Science. 2025. Vol. 266. P. 1330–1335.
An agglomerative pattern analysis algorithm is presented that groups objects using ordinal-invariant pattern clustering, with the goal of maximizing the coefficient of determination. Key stages are described: constructing initial pattern pattern by grouping objects according to permutations of feature values; computing centroids and variances; and defining a merge criterion based on the maximal increase in R2. Algorithmic details include incremental updates of cumulative statistics, enabling constant-time updates per merge. A complexity analysis shows that the basic implementation is cubic in the number of initial clusters, but filtering and priority queues can reduce the practical running time. Experimental evaluation on a synthetic dataset and on the red wine quality dataset from the UCI Machine Learning Repository compares the proposed method with k-nearest neighbours regression and standard regression methods, demonstrating consistently higher R2 scores.
Дильмухаметова Алия Мидхатовна, Напалков В. В., «Doklady Mathematics» 2012 Т. 443 № 3 С. 293–295
В данной работе введены обобщенные частные производные, изучены дифференциальные уравнения в обобщенных частных производных с постоянными коэффициентами и доказан фундаментальный принцип Эйлера для таких уравнений. Устанавливлена связь с классом уравнений в обычных частных производных с переменными коэффициентами. ...
Added: September 21, 2026
Springer, Cham, 2025.
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 6 P. 1–20
This study presents a unified low-parameter approach to multi-class classification of microorganisms (micrococci, diplococci, streptococci, and bacilli) based on automated machine learning. The method is designed to produce interpretable taxonomic descriptors through analysis of the external geometric characteristics of microorganisms, including cell shape, colony organization, and dynamic behavior in unfixed microscopic scenes. A key advantage ...
Added: September 21, 2026
Springer, 2026.
Two volumes of the SPECOM 2026 proceedings contain a collection of submitted papers presented at SPECOM 2026, which were thoroughly reviewed by members of the Program Committee and additional reviewers consisting of almost 80 experts in the conference topic areas. In total, 65 regular full papers out of 99 submissions made via the EasyChair electronic ...
Added: September 20, 2026
Medvedev V., Annals of Global Analysis and Geometry 2026 Vol. 70 No. 2 P. 8–23
This paper studies three-dimensional compact static manifolds with boundary and positive scalar curvature. We prove that, under a suitable bound on the Ricci curvature, the orientable quotient of the Nariai static manifold with boundary is the only such manifold with connected boundary, provided that the zero-level set of the potential is connected and does not intersect ...
Added: September 19, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2026 Vol. 36 No. 2 P. 323–334
In this paper, an improved approach for automatic wildlife detection in natural environments based on the integration of a neural network architecture with a two-stream attention mechanism and a novel preclassification step based on infrared data has been presented. The proposed method addresses one of the key challenges in environmental monitoring: the need for scalable ...
Added: September 19, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., Proceedings of the ACM on Management of Data, USA 2026 Vol. 4 No. 1 P. 1–28
Modern knowledge and large volumes of data are increasingly encoded within neural networks, making the task of simplifying their structures and reducing the number of parameters especially relevant, both to improve efficiency and to facilitate deployment in resource-constrained environments. This paper presents a novel approach to neural network compression that addresses redundancy at both the ...
Added: September 19, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2025 Vol. 35 No. 2 P. 148–158
This paper describes our research on creating classifiers for microbial images (micrococci microscopy images) obtained from pictures of unfixed microscopic scenes. In our work, we propose an AutoML approach based on the automatic generation and analysis of the feature space for constructing the most optimal descriptors of microorganism images for subsequent classification. This makes it ...
Added: September 19, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2026 Vol. 36 No. 2 P. 302–312
The lack of annotated microscopic datasets remains a major obstacle to training robust deep learning models for microbial classification. In this paper, a novel data augmentation pipeline that uses visual–linguistic large-scale models to generate synthetic microscopic images of six different bacterial and nonbacterial classes has been proposed. Synthetic samples have gradually been added to the ...
Added: September 19, 2026
Springer, Cham, 2026.
computer vision ...
Added: September 19, 2026
Springer, Cham, 2026.
Added: September 19, 2026
Aleskerov F. T., Khutorskaya O., Stepochkina A. et al., Springer, 2026.
The book contains new models of bibliometric analysis based on centrality measures in network analysis, pattern analysis and stability analysis. A distinctive feature of these centrality measures is that they account for the parameters of vertices and group influence of vertices to a vertex. This reveals specific groups of publications, authors, terms, journals and affiliations ...
Added: May 15, 2026
Alexey Myachin, Studies in Systems, Decision and Control 2025 Vol. 615 P. 12–20
In this paper, we introduce a refined and rigorous methodological framework for the validation and quality assessment of pattern analysis outcomes. Our approach synergistically integrates a formal algorithmic model with novel conceptual constructs - specifically, the notions of the empty pattern and pattern complexity. A comprehensive array of metric approaches is employed to evaluate pattern analysis ...
Added: November 5, 2025
Alexey Myachin, Procedia Computer Science 2024 Vol. 242 P. 95–99
A new method for searching patterns in data using interval estimates is proposed. The computational complexity, algorithmic implementation, and some properties that allow the method to be applied to high-dimensional data are described, including the characteristics of ordering the studied indicators in groups obtained from the analysis, the unambiguous definition of such groups, and their ...
Added: August 26, 2024
Kazantseva A., Enikeeva R., Alla V. Toropova et al., Research Results in Biomedicine 2023 Vol. 9 No. 2 P. 181–190
Background: Existing genetic studies on musical abilities have focused on various molecular approaches, which determined gene regions/variants implicated in (i) music perception and performance based on genome-wide linkage and association scans, (ii) differential expression patterns as a response to music listening/performance, (iii) music production in songbirds, and (iiii) neuronal plasticity relation to music training. The ...
Added: November 30, 2023
Dmitrienko A., Myachin A. L., Университетское управление: практика и анализ 2023 Т. 27 № 2 С. 75–88
The paper analyzes the pricing strategies of Russian public universities in the context of the influence of competitors on the market for tuition-paying education. The aim of the study is to determine how competition in local higher education markets affects the pricing strategies of Russian public universities. The empirical basis of the study is formed ...
Added: June 7, 2023
Myachin A. L., , in: Intelligent Computing: Proceedings of the 2022 Computing Conference, Volume 1.: Springer, 2022. P. 826–835.
We present methods for finding patterns using sorting algorithms. Two modifications of diffusion-invariant pattern clustering are proposed, which allow finding structurally similar objects under study. The proposed modifications allow you to reduce the time spent on searching for templates, which allows you to work with big datasets. It assumes endogenous quantification and distribution of income ...
Added: December 3, 2022
Moeyaert M., Akhmedjanova D., Ferron J. et al., Evidence-Based Communication Assessment and Intervention 2020 Vol. 14 No. 1-2 P. 28–51
The methodology of single-case experimental designs (SCED) has been expanding its efforts toward rigorous design tactics to address a variety of research questions related to intervention effectiveness. Effect size indicators appropriate to quantify the magnitude and the direction of interventions have been recommended and intensively studied for the major SCED design tactics, such as reversal ...
Added: October 11, 2022
Prokofiev V. N., Myachina K., Myachin A. L., Control Sciences 2021 Vol. 3 P. 50–57
The indicators of regional sports development in the Russian Federation are analyzed to find regions with a similar sports development strategy (according to the chosen methodology and measures of closeness) and to identify dynamic groups in a four-year period. Some clustering and pattern analysis methods are described, and their use in the study is validated. ...
Added: October 24, 2021
Myachin A. L., Prokofiev V. N., Степанов А. А., Управление большими системами: сборник трудов 2021 № 92 С. 43–63
The study is devoted to the application of ordinal-fixed and ordinal-invariant pattern clustering to study the structure of the energy sector in regions of Russian Federation over a five-year period. Methods for pattern analysis in the work are due to the independence of the final results from the difference in the absolute values of indicators ...
Added: September 1, 2021
Prokofiev V. N., Myachin A. L., Myachina K., Проблемы управления 2021 Т. 3 С. 50–57
The indicators of regional sports development in the Russian Federation are analyzed
to find regions with a similar sports development strategy (according to the chosen methodology
and measures of closeness) and to identify dynamic groups in a four-year period. Some clustering
and pattern analysis methods are described, and their use in the study is validated. The results
obtained by ...
Added: June 29, 2021
Myachin A. L., Akhremenko A. S., , in: Intelligent Methods in Computing, Communications and ControlVol. 1243.: Springer, 2021. P. 198–205.
This work is devoted to the methodology for identifying structurally
close objects of the type “country_year” based on a system of indicators characterizing
the state capacity 1996–2015. A comparison of clustering methods
(including hierarchical clustering) with methods of analyzing patterns based on
a pairwise comparison of indicators, ordinal-fixed and ordinal-invariant pattern
clustering, is proposed. The possibility of sharing the methods ...
Added: September 24, 2020
Myachin A. L., , in: Proceedings of the 20th International Conference on Group Decision and Negotiation.: Ryerson University, 2020. P. 22.1–22.10.
The paper describes the assessment of data on the innovation development of individual countries and regions, taking into account a large number of different indicators. An overview of international and national approaches to the assessment of innovative development is presented: Global Innovation Index (Cornell University, INSEAD, and the World Intellectual Property Organization); Portfolio Innovation Index ...
Added: June 2, 2020
Akhremenko A. S., Myachin A. L., Политическая наука 2019 № 3 С. 112–139
The central focus of this paper is a methodological one. Using the set of indicators
of state capacity, we demonstrate a specific strategy for identifying sustainable
structures in multidimensional data sets that reflect complex and ambiguous concepts of
political science. A key feature of this strategy is the application of related, but significantly
different technically, multidimensional methods – cluster ...
Added: December 9, 2019