文献类型：会议论文

英文题名：Microarray Classification with Noise via Weighted Adaptive Elastic Net

作者：Li, Juntao[1];Wang, Jingxuan[2];Zheng, Yuhan[3];Xiao, Huimin[1]

通讯作者：Li, JT[1]

机构：[1]Henan Univ Econ & Law, Coll Comp & Informat Engn, Zhengzhou 450002, Henan, Peoples R China;[2]Capital Med Univ, Beijing Obstet & Gynecol Hosp, Beijing 100026, Peoples R China;[3]Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Peoples R China

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]corresponding author), Henan Univ Econ & Law, Coll Comp & Informat Engn, Zhengzhou 450002, Henan, Peoples R China.|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

会议论文集：6th IEEE Data Driven Control and Learning Systems Conference (DDCLS)

会议日期：MAY 26-27, 2017

会议地点：Chongqing, PEOPLES R CHINA

语种：英文

外文关键词：Microarray classification; Weighted adaptive elastic net; Gene selection; Noise

摘要：The adaptive elastic net has been widely studied in the microarray classification due to the elegant performances in gene selection. However, the classification accuracy will be affected if the noise is included. As such, this paper proposes a weighted adaptive elastic net for the binary microarray classification with noise by using the distances from the sample points to both class centers. Furthermore, the performance of adaptive gene selection is proved and the solution path algorithm is developed. Finally, the results on two cancer data added 4 additional samples illustrate that the weighted adaptive elastic net can achieve considerable classification accuracy and select the genes related with diseases.