Please use this identifier to cite or link to this item:
|Title:||Clustering in dimension reduction for function approximation problem|
|Authors:||Burnaev, E. V.|
Prihodko, P. V.
|Keywords:||ЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Информатика|
|Abstract:||In order to reduce the dimension of input vectors before construction of ap-proximation MAVE-type methods (minimum average variance estimation) can be used, however they are very computationally intensive. In the present work the modification of method MAVE is described which allows substantial decrease of algorithm run time at the expense of small error increase.|
|Appears in Collections:||Section 8. COMPUTER DATA ANALYSIS IN APPLICATIONS|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.