| DC Field | Value | Language |
|---|
| dc.contributor.author | Krasnoproshin, V. | - |
| dc.contributor.author | Rodchenko, V. | - |
| dc.contributor.author | Karkanitsa, A. | - |
| dc.date.accessioned | 2021-11-05T11:07:16Z | - |
| dc.date.available | 2021-11-05T11:07:16Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.citation | Krasnoproshin, V. Pattern Recognition Based on Classes Distinctive Features / Krasnoproshin V., Rodchenko V., Karkanitsa A. // Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021) : Proceedings of the 15th International Conference, 21–24 Sept. 2021, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2021. – P. 22–24. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/45828 | - |
| dc.description.abstract | In pattern recognition, the approach where Supervised Learning is reduced to the construction of decision rules is considered to be classical. These rules should ensure an extremum of some criterion. The paper proposes an alternative solution based on the search for combinations of features that ensure classes separation. The results of a numerical experiment on model data confirm the effectiveness of the proposed approach. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | UIIP NASB | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | conference proceedings | ru_RU |
| dc.subject | pattern recognition | ru_RU |
| dc.subject | classification | ru_RU |
| dc.subject | instance-based learning | ru_RU |
| dc.subject | discovering patterns | ru_RU |
| dc.title | Pattern Recognition Based on Classes Distinctive Features | ru_RU |
| dc.type | Статья | ru_RU |
| Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021)
|
