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Journal of Automation and Information Sciences

Выходит 12 номеров в год

ISSN Печать: 1064-2315

ISSN Онлайн: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

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Information Technology of Separating Hyperplanes Synthesis for Linear Classifiers

Том 51, Выпуск 5, 2019, pp. 54-64
DOI: 10.1615/JAutomatInfScien.v51.i5.50
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Краткое описание

Information technology allowing one to implement the tasks of classification, clustering, studying the topology of the data of the information component is proposed. The multidimensional feature space is reduced to the visual presentation space to determine the information content of the data. Optimized reduction of the space dimension to two-dimensional one applying multidimensional scaling methods is used. Visual definition of grouping data allows separating areas to form. The next stage is visual limitation of categories of classes using graphic separators. To enable flexibility of nonlinear areas limitation a combination of linear ones is used, thereby forming a piecewise linear set with necessary degree of sampling. Using piecewise linear constraints allows us to implement projecting into original multidimensional feature space. Visual construction of restrictive separators makes it possible to consider tolerance fields of changing of features parameters, separation measure of classes, nonlinearity of data grouping. This is followed by reverse expansion of space with the projection of the separators into n -dimensional space with the separating hyperspace synthesis. Thus the limitative areas of hyperspace for the necessary categories of classes are formed. At the same time the visualization of classification process in a hyperspace is provided. The information technology base is the multidimensional space projection into visual (two-dimensional) space construction piecewise linear limiters of studied areas, subsequent limiters projecting into multidimensional space. Thus the information technology enables us to synthesize separating hyperplanes limiting categories of classes in multidimensional space. The technology application successive stages are described.

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ЦИТИРОВАНО В
  1. Krak Iu., Kruchynin K., Barmak O., Manziuk E., Kruchinin S. P., Visual Analytics in Machine Training Systems for Effective Decision, in Advanced Nanomaterials for Detection of CBRN, 2020. Crossref

  2. Barmak O.V., Manziuk E.A. , Kalyta O.D. , Krak Iu. , Kuznetsov V.O. , Kulias A.I. , Recognition of emotional expressions using the grouping crowdings of characteristic mimic states, PROBLEMS IN PROGRAMMING, 2-3, 2020. Crossref

  3. Barmak Olexander, Kalyta Oleg, Krak Iurii, Manziuk Eduard, Kuznetsov Vladyslav, Model of the Facial Emotions Expressions Based on Grouping Classes of Feature Vectors, in Lecture Notes in Computational Intelligence and Decision Making, 1246, 2021. Crossref

  4. Kondratiuk Serhii, Krak Iurii, Kylias Anatolii, Kasianiuk Veda, Fingerspelling Alphabet Recognition Using CNNs with 3D Convolutions for Cross Platform Applications, in Lecture Notes in Computational Intelligence and Decision Making, 1246, 2021. Crossref

  5. Krak Iurii, Kulias Anatoliy, Petrovych Valentina, Kuznetsov Vladyslav, About Methods for Classifying Hidden Language Concepts in Specialized Texts Involving Pseudoinverse, Clustering and Data Grouping, Cybernetics and Computer Technologies, 2, 2021. Crossref

  6. Radiuk Pavlo, Barmak Olexander, Krak Iurii, An Approach to Early Diagnosis of Pneumonia on Individual Radiographs based on the CNN Information Technology, The Open Bioinformatics Journal, 14, 1, 2021. Crossref

  7. Krak Iurii V., Barmak Olexander V., Manziuk Eduard, Visual Analytics to Build a Machine Learning Model, in Research Advancements in Smart Technology, Optimization, and Renewable Energy, 2021. Crossref

  8. Yaremenko Serhii, Krak Iurii, Determination of the Position of the Laser Spot in the Plane of the Photo Sensor of the Multimedia Shooting Gallery, IEEE EUROCON 2021 - 19th International Conference on Smart Technologies, 2021. Crossref

  9. Manziuk Eduard, Barmak Olexander, Krak Iurii, Mazurets Olexander, Pylypiak Olexander, Method of features analysis on transition data, 2021 IEEE 3rd International Conference on Advanced Trends in Information Theory (ATIT), 2021. Crossref

  10. Barmak Olexander, Manziuk Eduard, Krak Iurii, Classification Based Hierarchical Clustering Prediction Variability in the Ensembles of Models Using a Statistical Approach, 2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT), 2020. Crossref

  11. Krak Iurii, Barmak Olexander, Manziuk Eduard, Using visual analytics to develop human and machine‐centric models: A review of approaches and proposed information technology, Computational Intelligence, 38, 3, 2022. Crossref

  12. Neskorodieva Tetiana, Fedorov Eugene, Neural Network Models Ensembles for Generalized Analysis of Audit Data Transformations, in Mathematical Modeling and Simulation of Systems, 344, 2022. Crossref

  13. Yaremenko S., Krak Iu., Determining the Centroid of a Laser Spot in the Plane of a Multimedia Shooting Gallery Sensor Based on the Methods of Interpolation and Filtering of the Image Fragment, Cybernetics and Systems Analysis, 58, 4, 2022. Crossref

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