SOM2CE: Double self-organizing map based cluster ensemble framework and its application in cancer gene expression profiles

Zhiwen Yu, Hantao Chen, Jia You, Le Li, Guoqiang Han

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)

Abstract

Though there exist a lot of cluster ensemble approaches, few of them consider how to degrade the effect of noisy attributes in the dataset. In the paper, we propose a new cluster ensemble framework, named as double self-organizing map based cluster ensemble (SOM2CE) to perform clustering on noisy datasets. SOM2CE incorporates the self-organizing map (SOM) twice into the ensemble framework to discovery the underlying structure of noisy datasets, which applies SOM to perform clustering not only on the sample dimension, but also on the attribute dimension. SOM2CE also adopts the normalized cut algorithm to partition the consensus matrix constructed from multiple clustering solutions, and obtain the final results. Experiments on both synthetic datasets and cancer gene expression profiles illustrate that the proposed approach not only achieves good performance on synthetic datasets and cancer gene expression profiles, but also outperforms most of the existing approaches in the process of clustering gene expression profiles.
Original languageEnglish
Title of host publicationAdvanced Research in Applied Artificial Intelligence - 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Proceedings
Pages351-360
Number of pages10
DOIs
Publication statusPublished - 1 Aug 2012
Event25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012 - Dalian, China
Duration: 9 Jun 201212 Jun 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7345 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012
Country/TerritoryChina
CityDalian
Period9/06/1212/06/12

Keywords

  • cancer data
  • Cluster ensemble
  • self-organizing map

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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