?
Towards polynomial subgroup discovery by means of FCA?
P. 57–68.
The goal of subgroup discovery is to find groups of objectsthat are significantly different than “average” object w.r.t. some super-vised information. It is a computational intensive procedure that tra-verses a large searching space corresponding to the set of formal con-cepts. It was recently found that a part of formal concepts, called stableconcepts, can be found in polynomial time. Accordingly, in this paper anew algorithm, calledSD-SOFIA, is presented.SD-SOFIAfits subgroup dis-covery process in the framework of stable concept search. The proposedalgorithm is evaluated on a dataset from UCI repository. It is shown thatits practical computational complexity is polynomial.
Sukhoverkhova D., Vyacheslav Mozolenko, Shchur L., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2025 Vol. 112 No. 4 Article 044128
We set out to explore the possibility of investigating the critical behavior of systems with first-order phase transition using deep machine learning. We propose a machine learning protocol with ternary classification of instantaneous spin configurations using known values of disordered phase energy and ordered phase energy. The trained neural network is used to predict whether ...
Added: October 18, 2025
Bernhardt B. D., Marciano C., Guarracino M. R., Operations Research Forum 2025 Vol. 6 Article 47
E-commerce is a key sector in the Italian economy, with online companies becoming some of the largest and most profitable businesses. However, this growth comes with increased risk exposure. This study aims to investigate the relationship between alternative data (contextual factors, Text-Driven Data Enrichment) and the probability of default for Italian e-commerce companies. To date, ...
Added: September 6, 2025
D. D. Sukhoverkhova, L. N. Shchur, Lobachevskii Journal of Mathematics 2025 Vol. 46 No. 1 P. 528–534
We investigate the possibility of extracting features of second-order phase transitions using transfer machine learning. We have performed supervised machine learning for binary classification of snapshots of the spin distribution of the isotropic Ising model. The binary classification is performed in ferromagnetic and paramagnetic phases using a known critical temperature. The trained network is used ...
Added: January 13, 2025
Sukhoverkhova D., Mozolenko V., Shchur L., / Series arXiv "math". 2024. No. 2411.00733.
We set out to explore the possibility of investigating the critical behavior of systems with first-order phase transition using deep machine learning. We propose a machine learning protocol with ternary classification of instantaneous spin configurations using known values of disordered phase energy and ordered phase energy. The trained neural network is used to predict whether ...
Added: November 4, 2024
Chertenkov V., Burovskiy E., Shchur L., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2023 Vol. 108 No. 3 Article L032102
We analyze the problem of supervised learning of ferromagnetic phas transitions from the statistical physics perspective. We consider two systems in two universality classes, the two-dimensional Ising model and two-dimensional Baxter-Wu model, and perform careful finite-size analysis of the results of the supervised learning of the phases of each model. We find that the variance ...
Added: September 19, 2023
Iu. Nasu, V. V. Lanin, Proceedings of the Institute for System Programming of the RAS 2023 Vol. 35 No. 2 P. 49–56
This paper was prepared while developing text classification system for legal documents, especially those that issued by Legislative Assembly of Perm Krai. The problem in question is a lack of solutions that meet regional requirements, the main of which is the classification used in region. The research that evaluates applications of Natural Language Processing models ...
Added: July 4, 2023
Jyoti -., Buzmakov Aleksey, Kailasam S., , in: The 15th International Conference on Concept Lattices and Their Applications CLA2020Issue 2668.: CEUR-WS, 2020. P. 287–292.
Added: July 10, 2021
Stukal D., Беленков В. Е., Philippov I., Политическая наука 2021 № 1 С. 46–75
Появление и рост популярности социальных сетей, а также растущая цифровизация, проникающая в разнообразные сферы экономики и общества оказали существенное влияние на сферу политики в целом и, в частности, на процессы политической мобилизации и коммуникации. Методологический арсенал политической науки также оказался затронут указанными трансформационными процессами и начал пополняться новыми подходами и методами, предложенными в рамках недавно ...
Added: March 2, 2021
Cham: Springer, 2020.
This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020.
The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a ...
Added: May 17, 2020
Romanov A., Ekaterina Kozlova, Lomotin Konstantin, , in: Digital Transformation and Global Society. Third International Conference, DTGS 2018, St. Petersburg, Russia, 2018, Revised Selected Papers. Part II. Communications in Computer and Information Science 859Issue 859.: Springer, 2018. P. 310–323.
This research is dedicated to the design of a decision support system for categorization of scientific literature. The purpose of this work is to research possible ways to apply the machine learning algorithms to the automation of manual text categorization. The following stages are considered: preprocessing of raw data, word embedding, model selection, classification model, ...
Added: August 26, 2019
Korepanova N., , in: Proceedings of the first Workshop on Data Analysis in Medicine (WDAM-2017)Issue 6.: EasyChair, 2018. P. 48–53.
Modern medicine aspire to improve the effectiveness of treatment for some diseases through, so called, personalized medicine. However, totally personalized medicine or personalized treatment of even one disease is a very ambitious goal. Subgroup analysis of patients is a preliminary step to the total personalization. Several completely different views on the principles and usefulness of ...
Added: June 9, 2018
Alam M., Buzmakov A. V., Napoli A., Discrete Applied Mathematics 2018 Vol. 249 P. 2–17
With an increased interest in machine processable data and with the progress of semantic technologies, many datasets are now published in the form of RDF triples for constituting the so-called Web of Data. Data can be queried using SPARQL but there are still needs for integrating, classifying and exploring the data for data analysis and ...
Added: September 26, 2017
Iscan Z., Yüksel A., Dokur Z. et al., Digital Signal Processing 2009 Vol. 19 No. 5 P. 890–901
In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional ...
Added: January 22, 2015
Dubrova T. A., В кн.: Математико-статистический анализ социально-экономических процессов. Межвузовский сборник научных трудов. Выпуск 8.: М.: Издательство МГУЭСИ, 2011. С. 48–53.
Added: November 26, 2013