文献类型：会议论文

英文题名：Gene Selection for Cancer Classification Using Improved Group Lasso

作者：Li, Juntao[1];Dong, Wenpeng[1];Meng, Deyuan[2];Xiao, Huimin[3]

第一作者：Li, Juntao

通讯作者：Li, JT[1]

机构：[1]Henan Normal Univ, Sch Math & Informat Sci, Henan Engn Lab Big Data Stat Anal & Optimal Contr, Xinxiang 453007, Peoples R China;[2]Beihang Univ BUAA, Res Div 7, Beijing 100191, Peoples R China;[3]Henan Univ Econ & Law, Coll Comp & Informat Engn, Zhengzhou 450002, Peoples R China

第一机构：Henan Normal Univ, Sch Math & Informat Sci, Henan Engn Lab Big Data Stat Anal & Optimal Contr, Xinxiang 453007, Peoples R China

通讯机构：[1]corresponding author), Henan Normal Univ, Sch Math & Informat Sci, Henan Engn Lab Big Data Stat Anal & Optimal Contr, Xinxiang 453007, Peoples R China.

会议论文集：28th Chinese Control and Decision Conference

会议日期：MAY 28-30, 2016

会议地点：Yinchuan, PEOPLES R CHINA

语种：英文

外文关键词：Cancer classification; Gene selection; Conditional mutual information; Group lasso

摘要：An improved group lasso is proposed for simultaneous cancer classification and gene selection. A new criterion is firstly proposed to evaluate the individual gene importance by using the conditional mutual information. Then the weights with biological explanation are constructed and the improved group lasso is presented. A blockwise descent algorithm for solving the proposed model is also developed. The experimental results on lung cancer and prostate cancer data sets demonstrate that the proposed method can effectively perform classification and gene selection.