Regularization in discriminant analysis: An overview

被引：20
|
作者：
Mkhadri, A [1 ]
Celeux, G [1 ]
Nasroallah, A [1 ]
机构：
[1] CADI AYYAD UNIV,MARRAKECH,MOROCCO
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 1997年 / 23卷 / 03期
关键词：
regularized discriminant analysis; predictive discrimination; spectral decomposition; dependence tree; ridge logistic model;
D O I：
10.1016/S0167-9473(96)00043-6
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper presents an overview of regularized techniques in discriminant analysis. The case of continuous variables is treated first, and then the case of discrete variables. Three types of approaches are distinguished: combining standard methods, constraining models and Bayesian modelling. We include numerical experiments to assess the efficiency of regularized versions of predictive discrimination and to illustrate the superiority of regularization on variable subset selection in a small sample setting.
引用
收藏
页码：403 / 423
页数：21
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