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Problems of Fuzzy c-Means Clustering and Similar Algorithms with High Dimensional Data Sets

Winkler, Roland and Klawonn, Frank and Kruse, Rudolf (2010) Problems of Fuzzy c-Means Clustering and Similar Algorithms with High Dimensional Data Sets. In: Advances in Data Analysis, Data Handling and Business Intelligence. Sringer. 34th Annual Conference GfKl 2010, 3rd German-Japanese Workshop, 20.-23. Jul 2010, Karlsruhe.

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Abstract

Fuzzy c-Means and its derivatives work very well on most clustering problems. However, FcM and many similar algorithms have their problems with high dimensional data sets and a large number of prototypes. Similar algorithms in this context are those, which generate fuzzy membership values by using a ratio of distances to ensure a sum of membership values of 1. Possibilistic clustering is explicitly of no concern because the degrees of possibility are computed for each cluster individually. In this paper, we exploit some structural problems using the ratio of distances as normalisation method in high dimensional spaces. We also show that a high number of prototypes influences the clustering procedure in a similar way as a high number of dimensions. Both effects are not entirely independent since the number of dimensions can be effectively reduced if the number of prototypes is smaller than the number of dimensions.

Item URL in elib:https://elib.dlr.de/64654/
Document Type:Conference or Workshop Item (Speech, Paper)
Title:Problems of Fuzzy c-Means Clustering and Similar Algorithms with High Dimensional Data Sets
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Winkler, Rolandroland.winkler (at) dlr.deUNSPECIFIED
Klawonn, Frankf.klawonn (at) fh-wolfenbuettel.deUNSPECIFIED
Kruse, Rudolfkruse (at) iws.cs.uni-magdeburg.deUNSPECIFIED
Date:July 2010
Journal or Publication Title:Advances in Data Analysis, Data Handling and Business Intelligence
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Publisher:Sringer
Series Name:Studies in Classification, Data Analysis, and Knowledge Organization
Status:Published
Keywords:Fuzzy c-means, clustering, high dimensionsional data sets
Event Title:34th Annual Conference GfKl 2010, 3rd German-Japanese Workshop
Event Location:Karlsruhe
Event Type:international Conference, Workshop
Event Dates:20.-23. Jul 2010
Organizer:German Classification Society
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:ATM and Operation (old)
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Effiziente Flugführung und Flugbetrieb (old)
Location: Braunschweig
Institutes and Institutions:Institute of Flight Control > Air traffic systems
Deposited By: Winkler, Roland
Deposited On:24 Aug 2010 14:07
Last Modified:31 Jul 2019 19:28

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