Random Vector Clustering Using Fuzzy C-Means

Richard J. Hathaway; Gerald Wesley Rogers; James C. Bezdek

doi:10.1109/NAFIPS.1998.715575

Random Vector Clustering Using Fuzzy C-Means

Richard J. Hathaway, Gerald Wesley Rogers, James C. Bezdek

Mathematical Sciences

Research output: Contribution to conference › Presentation

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 language	American English
DOIs	https://doi.org/10.1109/NAFIPS.1998.715575
State	Published - Aug 20 1998
Event	1998 Conference of the North American Fuzzy Information Processing Society (NAFIPS) - Duration: Aug 20 1998 → …

Conference

Conference	1998 Conference of the North American Fuzzy Information Processing Society (NAFIPS)
Period	08/20/98 → …

Disciplines

Education
Mathematics

Keywords

FCM
Fuzzy c-means

Access to Document

10.1109/NAFIPS.1998.715575License: Unspecified

Cite this

@conference{ac988db208cc46fc8aa8240e85731ac0,

title = "Random Vector Clustering Using Fuzzy C-Means",

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.",

keywords = "FCM, Fuzzy c-means",

author = "Hathaway, {Richard J.} and Rogers, {Gerald Wesley} and Bezdek, {James C.}",

year = "1998",

month = aug,

day = "20",

doi = "10.1109/NAFIPS.1998.715575",

language = "American English",

note = "1998 Conference of the North American Fuzzy Information Processing Society (NAFIPS) ; Conference date: 20-08-1998",

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TY - CONF

T1 - Random Vector Clustering Using Fuzzy C-Means

AU - Hathaway, Richard J.

AU - Rogers, Gerald Wesley

AU - Bezdek, James C.

PY - 1998/8/20

Y1 - 1998/8/20

N2 - 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.

AB - 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.

KW - FCM

KW - Fuzzy c-means

UR - https://digitalcommons.georgiasouthern.edu/math-sci-facpubs/159

UR - https://doi.org/10.1109/NAFIPS.1998.715575

U2 - 10.1109/NAFIPS.1998.715575

DO - 10.1109/NAFIPS.1998.715575

M3 - Presentation

T2 - 1998 Conference of the North American Fuzzy Information Processing Society (NAFIPS)

Y2 - 20 August 1998

ER -

Random Vector Clustering Using Fuzzy C-Means

Abstract

Conference

Disciplines

Keywords

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