Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification

Yang, Aijun1,2; Jiang, Xuejun3; Shu, Lianjie4; Liu, Pengfei5

2019-01-02

10.1080/03610926.2018.1463385

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS   影响因子和分区

0361-0926

1532-415X

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.

Sparse Bayesian method multicategory support vector machine correlation prior high-dimensional data classification

SCI ; CPCI-S ; EI

英语

通讯

Natural Science Foundation of Guangdong[2016A030313856]

Mathematics

Statistics & Probability

WOS:000466865100014

TAYLOR & FRANCIS INC

20182905549906

Bayesian networks ; Clustering algorithms ; Diseases ; Gene expression ; Regression analysis

Biology:461.9 ; Computer Software, Data Handling and Applications:723 ; Information Sources and Analysis:903.1 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4 ; Mathematical Statistics:922.2

MATHEMATICS

Web of Science

1.Nanjing Forestry Univ, Coll Econ & Management, Nanjing, Jiangsu, Peoples R China
2.State Stat Bur, Key Lab Stat Informat Technol & Data Min, Chengdu, Sichuan, Peoples R China
3.South Univ Sci & Technol China, Dept Math, Shenzhen, Peoples R China
4.Univ Macau, Fac Business Adm, Macau, Peoples R China
5.Jiangsu Normal Univ, Sch Math & Stat, Xuzhou, Jiangsu, Peoples R China

Yang, Aijun,Jiang, Xuejun,Shu, Lianjie,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.

Yang, Aijun,Jiang, Xuejun,Shu, Lianjie,&Liu, Pengfei.(2019).Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification.COMMUNICATIONS IN STATISTICS-THEORY AND METHODS,48(1),165-176.

Yang, Aijun,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.