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Random vector clustering using fuzzy c-means

  • Richard J. Hathaway
  • , G. Wesley Rogers
  • , James C. Bezdek
  • Georgia Southern University
  • University West of Florida

Research output: Contribution to book or proceedingConference articlepeer-review

Abstract

The fuzzy c-means (FCM) clustering algorithm has long been used to cluster numerical data. Recently FCM has also been used to cluster data sets consisting of mixtures of numerical, interval, and fuzzy data. Here the range of applicability of FCM is shown to include data sets whose feature values are continuous random variables. Parametric and nonparametric approaches are given and demonstrated using a simple computational example.

Original languageEnglish
Title of host publication1998 Conference of the North American Fuzzy Information Processing Society, NAFIPS 1998
EditorsLawrence O. Hall, Jim Bezdek
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages251-255
Number of pages5
ISBN (Electronic)0780344537
DOIs
StatePublished - 1998
Event1998 Conference of the North American Fuzzy Information Processing Society, NAFIPS 1998 - Pensacola Beach, United States
Duration: Aug 20 1998Aug 21 1998

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

Conference1998 Conference of the North American Fuzzy Information Processing Society, NAFIPS 1998
Country/TerritoryUnited States
CityPensacola Beach
Period08/20/9808/21/98

Scopus Subject Areas

  • General Computer Science
  • General Mathematics

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