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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/54456
Title: Synthesis of Automatic Recognition Systems Based on Properties Commonality
Authors: Krasnoproshin, V.
Rodchenko, V.
Karkanitsa, A.
Keywords: материалы конференций;pattern recognition system;data mining;instance-based learning
Issue Date: 2023
Publisher: BSU
Citation: Krasnoproshin, V. Synthesis of Automatic Recognition Systems Based on Properties Commonality / V. Krasnoproshin, V. Rodchenko, A. Karkanitsa // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 97–100.
Abstract: The paper explores an actual applied problem related to the synthesis of automatic recognition systems. The conceptual base of synthesis is determined by the methods of describing and separating classes. Three basic principles are known: enumeration of class members, commonality of properties, and clustering. The report proposes an original method for implementing the principle of commonality of properties, based on the search for combinations of features that provide classes distinguishing. The efficiency of the approach is confirmed by the results of a numerical experiment.
URI: https://libeldoc.bsuir.by/handle/123456789/54456
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)

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