DC Field | Value | Language |
dc.contributor.author | Krasnoproshin, V. | - |
dc.contributor.author | Rodchenko, V. | - |
dc.contributor.author | Karkanitsa, A. | - |
dc.coverage.spatial | Минск | en_US |
dc.date.accessioned | 2024-03-01T07:55:27Z | - |
dc.date.available | 2024-03-01T07:55:27Z | - |
dc.date.issued | 2023 | - |
dc.identifier.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. | en_US |
dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/54456 | - |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | BSU | en_US |
dc.subject | материалы конференций | en_US |
dc.subject | pattern recognition system | en_US |
dc.subject | data mining | en_US |
dc.subject | instance-based learning | en_US |
dc.title | Synthesis of Automatic Recognition Systems Based on Properties Commonality | en_US |
dc.type | Article | en_US |
Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)
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