Fuzzy clustering model of data with proportional membership

S. Nascimento, B. Mirkin, F. Moura-Pires

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

5 Citations (Scopus)

Abstract

The fuzzy clustering proportional membership (FCPM) proposes a model of how data are generated from a cluster structure to be identified. Clusters' prototypes and membership function are meaningful in the context of the model. In particular, the membership of an entity to a cluster expresses the proportion of the cluster's prototype reflected in the entity (proportional membership). In this work we explore the notion of proportional membership and compare it against the fuzzy c-means (FCM) distance membership. The ability of FCPM to reveal the underlying clustering model of data has been studied and a comparison with FCM had been performed as well.

Original languageEnglish
Title of host publicationPEACHFUZZ 2000: 19TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS
EditorsT. Whalen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages261-266
Number of pages6
ISBN (Print)0-7803-6274-8
DOIs
Publication statusPublished - 1 Jan 2000
Event19th International Confernce of the North American Fuzzy Information Processing Society-NAFIPS (PEACH FUZZ 2000) - Atlanta, GA, USA
Duration: 13 Jul 200015 Jul 2000

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISSN (Print)1098-7789

Conference

Conference19th International Confernce of the North American Fuzzy Information Processing Society-NAFIPS (PEACH FUZZ 2000)
CityAtlanta, GA, USA
Period13/07/0015/07/00

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    Nascimento, S., Mirkin, B., & Moura-Pires, F. (2000). Fuzzy clustering model of data with proportional membership. In T. Whalen (Ed.), PEACHFUZZ 2000: 19TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS (pp. 261-266). (Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NAFIPS.2000.877433