Sparse nonnegative matrix factorization with the elastic net

Weixiang Liu, Songfeng Zheng, Sen Jia, Linlin Shen, Xianghua Fu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Nonnegative matrix factorization is used extensively for feature extraction and clustering analysis. Recently many sparsity/sparseness constraints, such as L1 penalty, are introduced for sparse nonnegative matrix factorization. Inspired by sparsity measures from linear regression model, this paper proposes to integrate nonnegative matrix factorization with another sparsity constraint, the elastic net. The experimental results of clustering analysis on three gene expression datasets demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Pages265-268
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010 - Hong Kong, China
Duration: 18 Dec 201021 Dec 2010

Publication series

NameProceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

Conference

Conference2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Country/TerritoryChina
CityHong Kong
Period18/12/1021/12/10

Keywords

  • Clustering analysis
  • Gene expression data
  • Nonnegative matrix factorization
  • Sparsity penalty

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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