A new validity measure for a correlation-based fuzzy C-means clustering algorithm

Mingrui Zhang, Wei Zhang, Hugues Sicotte, Ping Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

One of the major challenges in unsupervised clustering is the lack of consistent means for assessing the quality of clusters. In this paper, we evaluate several validity measures in fuzzy clustering and develop a new measure for a fuzzy c-means algorithm which uses a Pearson correlation in its distance metrics. The measure is designed with within-cluster sum of square, and makes use of fuzzy memberships. In comparing to the existing fuzzy partition coefficient and a fuzzy validity index, this new measure performs consistently across six microarray datasets. The newly developed measure could be used to assess the validity of fuzzy clusters produced by a correlation-based fuzzy c-means clustering algorithm.

Original languageEnglish (US)
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Pages3865-3868
Number of pages4
DOIs
StatePublished - 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: Sep 2 2009Sep 6 2009

Other

Other31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
CountryUnited States
CityMinneapolis, MN
Period9/2/099/6/09

Fingerprint

Fuzzy clustering
Microarrays
Clustering algorithms
Cluster Analysis

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • Medicine(all)

Cite this

Zhang, M., Zhang, W., Sicotte, H., & Yang, P. (2009). A new validity measure for a correlation-based fuzzy C-means clustering algorithm. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 (pp. 3865-3868). [5332582] https://doi.org/10.1109/IEMBS.2009.5332582

A new validity measure for a correlation-based fuzzy C-means clustering algorithm. / Zhang, Mingrui; Zhang, Wei; Sicotte, Hugues; Yang, Ping.

Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. p. 3865-3868 5332582.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, M, Zhang, W, Sicotte, H & Yang, P 2009, A new validity measure for a correlation-based fuzzy C-means clustering algorithm. in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009., 5332582, pp. 3865-3868, 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009, Minneapolis, MN, United States, 9/2/09. https://doi.org/10.1109/IEMBS.2009.5332582
Zhang M, Zhang W, Sicotte H, Yang P. A new validity measure for a correlation-based fuzzy C-means clustering algorithm. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. p. 3865-3868. 5332582 https://doi.org/10.1109/IEMBS.2009.5332582
Zhang, Mingrui ; Zhang, Wei ; Sicotte, Hugues ; Yang, Ping. / A new validity measure for a correlation-based fuzzy C-means clustering algorithm. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 2009. pp. 3865-3868
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