Double partition around medoids based cluster ensemble

Le Li, Jia You, Guoqiang Han, Hantao Chen

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

2 Citations (Scopus)

Abstract

Cluster ensemble is one of the hot topics in the machine learning area. Though plenty of cluster ensemble methods and frameworks have been proposed, many cluster ensemble methods are easily faded by noisy datasets and local optimal problems. In this article, we introduced a novel cluster ensemble method, named as Double Partition Around Medoids based Cluster Ensemble (PAM2CE). PAM2CE will effectively weaken or even eliminate the effect of noisy datasets and local optimal problems via clustering attributes and selecting the representative attributes. The experimental results reveal the better robustness and effectiveness of proposed method.
Original languageEnglish
Title of host publicationProceedings of 2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012
Pages1390-1394
Number of pages5
Volume4
DOIs
Publication statusPublished - 31 Dec 2012
Event2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012 - Xian, Shaanxi, China
Duration: 15 Jul 201217 Jul 2012

Conference

Conference2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012
Country/TerritoryChina
CityXian, Shaanxi
Period15/07/1217/07/12

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Human-Computer Interaction

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