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Learning hypotheses from triadic labeled data
P. 474-480.
We propose extensions of the classical JSM-method andtheNa ̈ıveBayesianclassifierforthecaseoftriadicrelational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random Forest. In addition to classification precision and recall we also evaluated the time performance of the proposed methods.
Keywords: машинное обучениеклассификацияанализ формальных понятийFormal Concept Analysismachine learningтриадический анализ формальных понятийclassificationtriadic dataJSM methodДСМ-метод
Publication based on the results of:
In book
Los Alamitos, Washington, Tokyo : IEEE Computer Society, 2014
Zhuk R., Ignatov D. I., Konstantinova N., Procedia Computer Science 2014 Vol. 31 P. 928-938
We propose extensions of the classical JSM-method and the Na ̈ıve Bayesian classifier for the case of triadic relational data. We performed a series of experiments on various types of data (both real and synthetic) to estimate quality of classification techniques and compare them with other classification algorithms that generate hypotheses, e.g. ID3 and Random ...
Added: June 9, 2014
Kashnitsky Y., Ignatov D. I., Интеллектуальные системы. Теория и приложения 2015 Т. 19 № 4 С. 37-55
The paper makes a brief introduction into multiple classifier systems and describes a particular algorithm which improves classification accuracy by making a recommendation of an algorithm to an object. This recommendation is done under a hypothesis that a classifier is likely to predict the label of the object correctly if it has correctly classified its ...
Added: December 7, 2015
Елисеев Д. А., Romanov D. A., Открытые системы. СУБД 2018 № 2 С. 42-44
В сфере госзакупок обращаются огромные денежные средства, и сегодня прикладываются большие усилия для обеспечения мониторинга процесса выполнения контракта — своевременное управление рисками может позволить сэкономить миллиарды рублей. Точная модель автоматизированной оценки рискованности государственных контрактов, построенная на базе алгоритмов машинного обучения, может помочь повысить эффективность государственных закупок. ...
Added: December 19, 2018
Bulychev A., Сомов О. Д., В кн. : Информатика, управление и системный анализ: Труды V Всероссийской научной конференции молодых ученых с международным участием. : Ростов н/Д : Ростовский государственный экономический университет "РИНХ", 2018. С. 94-102.
In the process of developing an information system for logistics transportation, there is a need to determine the initial rating of the new carrier within the parent company. The presence of the rating helps to more accurately carry out the formation of orders and build forecasts of its interaction with the parent company in the ...
Added: September 3, 2019
Suvorova A., Смирнова К. Р., Будин Е. А. et al., Компьютерные инструменты в образовании 2018 № 3 С. 49-64
The article describes a student research project on predicting the class of a post on a social network based on its textual content. The features of the project are discussed as an integral part of the trajectory of teaching data analysis methods, including text analysis methods and tools that are often not included in machine ...
Added: January 28, 2019
Kitov V. V., Экономика, статистика и информатика. Вестник УМО 2016 № 4 С. 22-26
Gradient boosting method with random rotations is considered, where before training each base learner random rotation is applied to the feature space. The accuracy metric of the given method is estimated for a broad range of generated problems of binary classification. Obtained results are evaluated and recommendations given for application of this method. ...
Added: August 23, 2016
Emmanuel I. C., Mitrofanova E., / Cornell Tech. Series 4064475 "ArXiv Preprint". 2022.
The paper is devoted to the study of the model fairness and process fairness of the Russian demographic dataset by making predictions of divorce of the 1st marriage, religiosity, 1st employment and completion of education. Our goal was to make classifiers more equitable by reducing their reliance on sensitive features while increasing or at least ...
Added: May 31, 2022
CEUR-WS.org, 2020
The CLA conference is an international forum for researchers, practitioners and students dedicated to the practice of Formal Concept Analysis (FCA) and areas closely related to it, including data analysis and mining, information retrieval, knowledge management, knowledge engineering, logic, algebra and lattice theory.
The 15th of CLA, CLA 2020, was going to be held in Tallinn, Estonia ...
Added: October 30, 2020
Krylov V., Krylov S., Journal of Physics: Conference Series 2018 Т. 1117 № conference 1
Reservoir Computing (RC) is taking attention of neural networks structures developers because of machine learning algorithms are simple at the high level of generalization of the models. The approaches are numerous. RC can be applied to different architectures including recurrent neural networks with irregular connections that are called Echo State Networks (ESN). However, the existence ...
Added: November 15, 2018
Naidenova X., Buzmakov A. V., Parkhomenko V. et al., , in : Formal Concept Analysis for Knowledge Discovery. Proceedings of International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD 2017), Moscow, Russia, June 1, 2017. Vol. 1921.: CEUR-WS.org, 2017. P. 88-103.
Symbolic classifiers allow for solving classification task and provide the reason for the classifier decision. Such classifiers were studied by a large number of researchers and known under a number of names including tests, JSM-hypotheses, version spaces, emerging patterns, proper predictors of a target class, representative sets etc. Here we consider such classifiers with restriction ...
Added: March 14, 2018
Aksiotis V., Kharitonova A., Видяйкина А. А. et al., В кн. : Материалы Международного молодежного научного форума «ЛОМОНОСОВ-2022». : М. : МАКС Пресс, 2022. С. 1-2.
Numerous modern studies are aimed at creating a tool that is effective in classifying and recognizing emotions and their facial expressions based on electromyography (EMG). Technological developments in the field of virtual reality are underway to optimize human-computer interaction. Based on the results of changes in the electrical activity of the muscles, a judgment is ...
Added: October 26, 2022
Vlasenko D., Zaikin A., Zakharov D., Известия высших учебных заведений. Прикладная нелинейная динамика 2023 Т. 31 № 5 С. 661-669
Because the brain is an extremely complex hypernet of interacting macroscopic subnetworks, full-scale analysis of brain activity is a daunting task.Nevertheless,this task can be greatly simplified by analysing the correspondence between various patterns of macroscopic brain activity, forex ample,through functional magneticresonance imaging(fMRI) scans, and the performance of particular cognitive tasks or pathological states.The purpose of ...
Added: October 4, 2023
University Rennes 1, 2017
This volume is the supplementary volume of the 14th International Conference on Formal Concept Analysis (ICFCA 2017), held from June 13th to 16th 2017, at IRISA, Rennes. The ICFCA conference series is one of the major venues for researches from the field of Formal Concept Analysis and related areas to present and discuss their recent ...
Added: June 19, 2017
Kashnitsky Y., В кн. : Труды Международной конференции по физико-технической информатике CPT-2013, 12-19 мая 2013 г., Ларнака, Республика Кипр. : М., Протвино : Изд-во ИФТИ, 2013. С. 251-258.
Triclustering is an outgrowth of Formal Concept Analysis intented to detect groups of objects with similar properties (clusters) in a context of three sets of entities. In case of social network analysis,
for instance, these sets might be users, their interests and events they take part in. Triclustering here can help to detect users with similar ...
Added: January 27, 2014
Ignatov D. I., Gnatyshak D. V., Sergei O. Kuznetsov et al., Machine Learning 2015 Vol. 101 No. 1 P. 271-302
This paper presents several definitions of “optimal patterns” in triadic data and results of experimental comparison of five triclustering algorithms on real-world and synthetic datasets. The evaluation is carried over such criteria as resource efficiency, noise tolerance and quality scores involving cardinality, density, coverage, and diversity of the patterns. An ideal triadic pattern is a totally dense ...
Added: April 15, 2015
Kashnitsky Y., Kuznetsov S., , in : CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop Proceedings. Vol. 1624.: M. : Higher School of Economics, National Research University, 2016. Ch. 19. P. 189-202.
Nowadays decision tree learning is one of the most popular classification and regression techniques. Though decision trees are not accurate on their own, they make very good base learners for advanced tree-based methods such as random forests and gradient boosted trees. However, applying ensembles of trees deteriorates interpretability of the final model. Another problem is ...
Added: October 6, 2016
Kashnitsky Y., Ignatov D. I., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2014). Vol. 1257.: Prague : CEUR Workshop Proceedings, 2014. Ch. 3. P. 17-26.
The paper briefly introduces multiple classifier systems and describes a new algorithm, which improves classification accuracy by means of recommendation of a proper algorithm to an object classification. This recommendation is done assuming that a classifier is likely to predict the label of the object correctly if it has correctly classified its neighbors. The process ...
Added: September 12, 2014
Springer, 2021
This book constitutes the proceedings of the 16th International Conference on Formal Concept Analysis, ICFCA 2021, held in Strasbourg, France, in June/July 2021.
The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 32 submissions. The book also contains four invited contributions in full paper length.
The research part ...
Added: July 10, 2021
CEUR Workshop Proceedings, 2019
Added: October 31, 2019
Naidenova X., Ignatov D. I., Hershey : IGI Global, 2012
The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users’ requirements and the quality of solving targeted problems in domain applications.
Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and ...
Added: December 3, 2012
Kashnitsky Y., Kuznetsov S., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2016). : M. : [б.и.], 2016. P. 105-112.
Decision tree learning is one of the most popular classifica- tion techniques. However, by its nature it is a greedy approach to finding a classification hypothesis that optimizes some information-based crite- rion. It is very fast but may lead to finding suboptimal classification hy- potheses. Moreover, in spite of decision trees being easily interpretable, ensembles ...
Added: October 6, 2016
Лагутаева Д. А., Tretyak O., Григорьев А. Ю., Российский журнал менеджмента 2016 Т. 14 № 4 С. 3-20
This paper addresses the question of existence of relationships between usage of contemporary marketing practices and profitability for companies operating on the Russian market. To address this issue, we utilize an artificial intelligence method that so far was barely present in marketing and management science. The paper is not only promoting a novel research method, ...
Added: March 2, 2017
Lipatov M., Вестник Московского университета. Серия 1: Математика. Механика 2013 № 2 С. 39-42
We classify complex linear cocycles over ergodic automorphisms with the help of the barycenter method. A conjugating random matrix is built in explicit form. ...
Added: April 19, 2013
Karpychev V., Balatskaya A., Utyashev N. et al., Frontiers in Human Neuroscience 2022 No. 16 Article 984306
High-frequency oscillations (HFO) are a promising biomarker for the identification of epileptogenic tissue. While HFO rates have been shown to predict seizure outcome, it is not yet clear whether their morphological features might improve this prediction. We validated HFO rates against seizure outcome and delineated the distribution of HFO morphological features. We collected stereo-EEG recordings ...
Added: October 1, 2022