Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification
Aijun Yang1,2; Xuejun Jiang3; Lianjie Shu4; Pengfei Liu5
2019-01-02
Source PublicationCommunications in Statistics - Theory and Methods
ISSN1532415X 03610926
Volume48Issue:1Pages:165-176
Abstract

In this paper we introduce a sparse Bayesian kernel multinomial probit regression model for multi-class cancer classification. The relationship between the cancer types and gene expression measurements is explained by an unknown function which belongs to an abstract functional space like the reproducing kernel Hilbert space. We assign a sparse prior for regression parameters and perform variable selection by indexing the covariates of the model with a binary vector. The correlation prior for the binary vector assigned in this paper is able to distinguish models with the same size. The proposed method is successfully tested on one simulated data set and two publicly available real life data sets.

KeywordCorrelation Prior High-dimensional Data Classification Multicategory Support Vector Machine Sparse Bayesian Method
DOI10.1080/03610926.2018.1463385
URLView the original
Indexed BySCIE
Language英语
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000466865100014
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF ACCOUNTING AND INFORMATION MANAGEMENT
Corresponding AuthorXuejun Jiang
Affiliation1.College of Economics and Management,Nanjing Forestry University,,Nanjing,China
2.Key Laboratory of Statistical Information Technology and Data Mining,State Statistics Bureau,,Chengdu,China
3.Department of Mathematics,South University of Science and Technology of China,,Shenzhen,China
4.Faculty of Business Administration,University of Macau,,Macao
5.School of Mathematics and Statistics,Jiangsu Normal University,,Xuzhou,China
Recommended Citation
GB/T 7714
Aijun Yang,Xuejun Jiang,Lianjie Shu,et al. Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification[J]. Communications in Statistics - Theory and Methods,2019,48(1):165-176.
APA Aijun Yang,Xuejun Jiang,Lianjie Shu,&Pengfei Liu.(2019).Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification.Communications in Statistics - Theory and Methods,48(1),165-176.
MLA Aijun Yang,et al."Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification".Communications in Statistics - Theory and Methods 48.1(2019):165-176.
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