Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)

Cluster Tendency Assessment for Fuzzy Clustering of Incomplete Data

Authors
Ludmila Himmelspach, Daniel Hommers, Stefan Conrad
Corresponding Author
Ludmila Himmelspach
Available Online August 2011.
DOI
10.2991/eusflat.2011.136How to use a DOI?
Keywords
fuzzy cluster analysis, incomplete data, cluster tendency, cluster validity
Abstract

The quality of results for partitioning clustering algorithms depends on the assumption made on the number of clusters presented in the data set. Applying clustering methods on real data missing values turn out to be an additional challenging problem for clustering algorithms. Fuzzy clustering approaches adapted to incomplete data perform well for a given number of clusters. In this study, we analyse different cluster validity functions in terms of applicability on incomplete data on the one hand. On the other hand we analyse in experiments on several data sets to what extent the clustering results produced by fuzzy clustering methods for incomplete data reflect the distribution structure of data.

Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)
Series
Advances in Intelligent Systems Research
Publication Date
August 2011
ISBN
10.2991/eusflat.2011.136
ISSN
1951-6851
DOI
10.2991/eusflat.2011.136How to use a DOI?
Copyright
© 2011, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ludmila Himmelspach
AU  - Daniel Hommers
AU  - Stefan Conrad
PY  - 2011/08
DA  - 2011/08
TI  - Cluster Tendency Assessment for Fuzzy Clustering of Incomplete Data
BT  - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)
PB  - Atlantis Press
SP  - 290
EP  - 297
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2011.136
DO  - 10.2991/eusflat.2011.136
ID  - Himmelspach2011/08
ER  -