A Fuzzy Clustering Model of Data and Fuzzy c-Means

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66 Citations (Scopus)

Abstract

The multiple prototype fuzzy clustering model (FCMP), introduced by Nascimento, Mirkin and Moura-Pires (1999), proposes a framework for partitional fuzzy clustering which suggests a model of how the data are generated from a cluster structure to be identified. In the model, it is assumed that the membership of each entity to a cluster expresses a part of the cluster prototype reflected in the entity. In this paper we extend the FCMP framework to a number of clustering criteria, and study the FCMP properties on fitting the underlying proposed model from which data is generated. A comparative study with the fuzzy c-means algorithm is also presented
Original languageUnknown
Title of host publicationIEEE Neural Networks Council
Pages302-307
DOIs
Publication statusPublished - 1 Jan 2000
EventIEEE International Conference on Fuzzy Systems: Soft Computing in the Information Age (FUZZ-IEEE 2000) -
Duration: 1 Jan 2000 → …

Conference

ConferenceIEEE International Conference on Fuzzy Systems: Soft Computing in the Information Age (FUZZ-IEEE 2000)
Period1/01/00 → …

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