title: A L1-regularized feature selection method for local dimension reduction on microarray data.
abstract: Dimension reduction is a crucial technique in machine learning and data mining, which is widely used in areas of medicine, bioinformatics and genetics. In this paper, we propose a two-stage local dimension reduction approach for classification on microarray data. In first stage, a new L1-regularized feature selection method is defined to remove irrelevant and redundant features and to select the important features (biomarkers). In the next stage, PLS-based feature extraction is implemented on the selected features to extract synthesis features that best reflect discriminating characteristics for classification. The suitability of the proposal is demonstrated in an empirical study done with ten widely used microarray datasets, and the results show its effectiveness and competitiveness compared with four state-of-the-art methods. The experimental results on St Jude dataset shows that our method can be effectively applied to microarray data analysis for subtype prediction and the discovery of gene coexpression.
authors.affiliation: Department of Electronic Engineering, Xiamen University, Fujian 361005, China; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518000, China.
authors.forename: Shun
authors.initials: S
authors.lastname: Guo
authors.affiliation: Department of Electronic Engineering, Xiamen University, Fujian 361005, China. Electronic address: dhguo@xmu.edu.cn.
authors.forename: Donghui
authors.initials: D
authors.lastname: Guo
authors.affiliation: School of Mathematics and Computer Science, Fujian Normal University, Fujian, 350117, China.
authors.forename: Lifei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518000, China.
authors.forename: Qingshan
authors.initials: Q
authors.lastname: Jiang
mesh_terms: D057225:Data Mining / Q000379:methods* / Q000706:statistics & numerical data; D066264:Datasets as Topic / Q000145:classification*; D016014:Linear Models; D046228:Microarray Analysis
keywords: Classification; L1-regularized logistic regression; Local dimension reduction; Microarray data; Partial least squares (PLS)