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http://hdl.handle.net/11701/36150
Полная запись метаданных
Поле DC | Значение | Язык |
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dc.contributor.author | Ermakov, Sergey M. | - |
dc.contributor.author | Leora, Svetlana N. | - |
dc.date.accessioned | 2022-04-14T10:54:14Z | - |
dc.date.available | 2022-04-14T10:54:14Z | - |
dc.date.issued | 2022-03 | - |
dc.identifier.citation | Ermakov S.M., Leora S.N. On the choice of basic regression functions and machine learning. Vestnik of Saint Petersburg University. Mathematics. Mechanics. Astronomy, 2022, vol. 9 (67), issue 1, pp. 11–22. | en_GB |
dc.identifier.other | https://doi.org/10.21638/spbu01.2022.102 | - |
dc.identifier.uri | http://hdl.handle.net/11701/36150 | - |
dc.description.abstract | As is known, the regression analysis task is widely used in machine learning problems, which allows to establish relationship between observed data and compactly store of information. Most often, a regression function is described by a linear combination of some of the selected functions fj (X), j = 1, . . . ,m, X 2 D ⊂ Rs. If the observed data contains a random error, then the regression function restored from the observed data contains a random error and a systematic error depending on the selected functions fj . The article indicates the possibility of optimal selection of functions fj in the sense of a given functional metric, if it is known that the true dependence is consistent with some functional equation. In some cases (regular grids, s ≤ 2), similar results can be obtained using the random process analysis method. The numerical examples given in this article illustrate much more opportunities for the task of constructing the regression function. | en_GB |
dc.language.iso | ru | en_GB |
dc.publisher | St Petersburg State University | en_GB |
dc.relation.ispartofseries | Vestnik of St Petersburg University. Mathematics. Mechanics. Astronomy;Volume 9; Issue 1 | - |
dc.subject | regression analysis | en_GB |
dc.subject | approximation | en_GB |
dc.subject | basis functions | en_GB |
dc.subject | operator method | en_GB |
dc.subject | machine learning | en_GB |
dc.title | On the choice of basic regression functions and machine learning | en_GB |
dc.type | Article | en_GB |
Располагается в коллекциях: | Issue 1 |
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11-22.pdf | 598,79 kB | Adobe PDF | Просмотреть/Открыть |
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