计算机应用与软件2018，Vol.35Issue(3)：157-161,166,6.DOI:10.3969/j.issn.1000-386x.2018.03.030
基于图正则平滑低秩表示的基因表达谱特征选择
FEATURE SELECTION OF GENE EXPRESSION DATA BASED ON SMOOTHED LOW-RANK WITH GRAPH REGULARIZATION
摘要
Abstract
An improved feature selection algorithm of graph regularization smoothed low rank representation is proposed to solve the problem of inaccuracy of describing data structure using traditional low-rank representation.When constructing the objective function,the logarithm determinant function is used to do smoothing estimation instead of Kernel function,and manifold regularized item is added.The objective function is solved by ADM and the graph construction is restructured by a post-processing method.This algorithm can describe global subspace structure and partial linear structure accurately.After clustering experiment in gene expression profile and comparing with other feature selection algorithm,the results verify the effectiveness of the proposed approach.关键词
对数行列式/图正则/低秩表示/特征选择Key words
Logarithm determinant/Graph regularization/Low rank representation/Feature selection分类
信息技术与安全科学引用本文复制引用
杨国亮,康乐乐..基于图正则平滑低秩表示的基因表达谱特征选择[J].计算机应用与软件,2018,35(3):157-161,166,6.基金项目
国家自然科学基金项目(51365017) （51365017）
江西省教育厅科技计划项目(GJJ150680). （GJJ150680）
