Selecting informative variables in the identification problem

Описание

Тип публикации: статья из журнала

Год издания: 2016

Идентификатор DOI: 10.17516/1997-1397-2016-9-4-473-480

Ключевые слова: Classification, Informative variable, Optimization of the coefficient vector of the kernel fuzziness, Small training sample

Аннотация: The problem of multidimensional object classification with small training sample is considered. The following algorithms of estimating variable informativeness are considered: Ad, Del, AdDel. A new algorithm for selecting informative variables is proposed. It is based on the optimization of the coefficient vector of the kernel fuzzПоказать полностьюiness. Some modification of this algorithm is also discussed. The comparative analysis of existing methods for selecting informative variables is presented. © Siberian Federal University. All rights reserved.

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Издание

Журнал: Journal of Siberian Federal University - Mathematics and Physics

Выпуск журнала: Vol. 9, Is. 4

Номера страниц: 473-480

Персоны

  • Mihov Eugene D. (Institute of Space and Information Technology Siberian Federal University)
  • Nepomnyashchiy Oleg V. (Institute of Space and Information Technology Siberian Federal University)

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