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Simultaneous variable selection and class fusion with penalized distance criterion based classifiers

文献类型：期刊论文

作者Sheng, Ying1; Wang, Qihua1,2
刊名COMPUTATIONAL STATISTICS & DATA ANALYSIS
出版日期2019-05-01
卷号133页码:138-152
关键词Linear discriminant analysis Discriminant directions Variable selection Class fusion Misclassification error rate
ISSN号0167-9473
DOI10.1016/j.csda.2018.09.002
英文摘要Two new methods are proposed to solve the problem of constructing multiclass classifiers, selecting important variables for classification and determining corresponding discriminative variables for each pair of classes simultaneously in the high-dimensional setting. Different from existing methods, which are based on the separate estimation of the precision matrix and mean vectors, the proposed methods construct classifiers by estimating products of the precision matrix and mean vectors or all discriminant directions directly with appropriate penalties. This leads to the use of the distance criterion instead of the log-likelihood used in the existing literature. The proposed methods can not only consistently select important variables for classification but also consistently determine corresponding discriminative variables for each pair of classes. For the multiclass classification problem, conditional misclassification error rates of classifiers constructed by the proposed methods converge to the misclassification error rate of the Bayes rule in probability and rates of convergence are also obtained. Finally, simulations and the real data analysis well demonstrate good performances of the proposed methods in comparison with existing methods. (C) 2018 Elsevier B.V. All rights reserved.
资助项目National Natural Science Foundation of China[11871460] ; National Natural Science Foundation of China[11331011] ; program for Creative Research Group in China[61621003] ; Key Lab of Random Complex Structure and Data Science, CAS, China
WOS研究方向Computer Science ; Mathematics
语种英语
WOS记录号WOS:000460719200010
出版者ELSEVIER SCIENCE BV
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/33337]  
专题应用数学研究所
通讯作者Wang, Qihua
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Zhejiang Gongshang Univ, Sch Stat & Math, Hangzhou 310018, Zhejiang, Peoples R China
推荐引用方式
GB/T 7714		 Sheng, Ying,Wang, Qihua. Simultaneous variable selection and class fusion with penalized distance criterion based classifiers[J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS,2019,133:138-152.
APA Sheng, Ying,&Wang, Qihua.(2019).Simultaneous variable selection and class fusion with penalized distance criterion based classifiers.COMPUTATIONAL STATISTICS & DATA ANALYSIS,133,138-152.
MLA Sheng, Ying,et al."Simultaneous variable selection and class fusion with penalized distance criterion based classifiers".COMPUTATIONAL STATISTICS & DATA ANALYSIS 133(2019):138-152.

入库方式： OAI收割

来源：数学与系统科学研究院

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