Multinomial Regression with Elastic Net Penalty and Its Grouping Effect in Gene Selection

被引：0

作者：

Chen, Liuyuan ^{[1
,2
]}

Yang, Jie ^{[1
]}

Li, Juntao ^{[2
]}

Wang, Xiaoyu ^{[2
]}

机构：

[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Peoples R China

[2] Henan Normal Univ, Sch Math & Informat Sci, Xinxiang 453007, Peoples R China

来源：

ABSTRACT AND APPLIED ANALYSIS | 2014年

关键词：

SUPPORT VECTOR MACHINES; LOGISTIC-REGRESSION; VARIABLE SELECTION; CLASSIFICATION; REGULARIZATION; SVM;

D O I：

10.1155/2014/569501

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

For the multiclass classification problem of microarray data, a new optimization model named multinomial regression with the elastic net penalty was proposed in this paper. By combining the multinomial likeliyhood loss and the multiclass elastic net penalty, the optimization model was constructed, which was proved to encourage a grouping effect in gene selection for multiclass classification.

引用

页数：7

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