Selecting Informative Variables in the Identification Problem

被引：12
|
作者：
Mihov, Eugene D. [1 ]
Nepomnyashchiy, Oleg V. [1 ]
机构：
[1] Siberian Fed Univ, Inst Space & Informat Technol, Kirensky 26, Krasnoyarsk 660074, Russia
来源：
JOURNAL OF SIBERIAN FEDERAL UNIVERSITY-MATHEMATICS & PHYSICS | 2016年 / 9卷 / 04期
基金：
俄罗斯科学基金会;
关键词：
classification; small training sample; informative variable; optimization of the coefficient vector of the kernel fuzziness;
D O I：
10.17516/1997-1397-2016-9-4-473-480
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
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 fuzziness. Some modification of this algorithm is also discussed. The comparative analysis of existing methods for selecting informative variables is presented.
引用
收藏
页码：473 / 480
页数：8
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