title: |
M-Estimator induced Fuzzy Clustering Algorithms |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
| pages: | 298 - 304 | |
DOI: |
To be assigned soon (how to use a DOI) | |
author(s): |
Roland Winkler, Frank Klawonn, Rudolf Kruse |
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publication date: |
July 2011 |
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keywords: |
Fuzzy c-means, M-estimators, Robust
statistics, Noise clustering, Multiple prototypes |
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abstract: |
M-estimators can be seen as a special case of robust
clustering algorithms. In this paper, we present the
reversed direction and show that clustering algorithms can be constructed by using M-estimators.
A clever normalization is used to link the values
of several M-estimator prototypes together in one
clustering algorithm. A variety of M-estimators and
several normalization strategies are used in 4 data
sets to present their differences and properties. The
results are evaluated using 5 different clustering validation indices. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |