Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology

On the selection of m for Fuzzy c-Means

Authors
Vicenç Torra
Corresponding Author
Vicenç Torra
Available Online June 2015.
DOI
10.2991/ifsa-eusflat-15.2015.224How to use a DOI?
Keywords
Fuzzy clustering, Fuzzy c-means, parameters of FCM, m.
Abstract

Fuzzy c-means is a well known fuzzy clustering algorithm. It is an unsupervised clustering algorithm that permits us to build a fuzzy partition from data. The algorithm depends on a parameter m which corresponds to the degree of fuzziness of the solution. Large values of m will blur the classes and all elements tend to belong to all clusters. The solutions of the optimization problem depend on the parameter m. That is, different selections of m will typically lead to different partitions. In this paper we study and compare the effect of the selection of m obtained from the fuzzy c-means.

Copyright
© 2015, 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 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
Series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
10.2991/ifsa-eusflat-15.2015.224
ISSN
1951-6851
DOI
10.2991/ifsa-eusflat-15.2015.224How to use a DOI?
Copyright
© 2015, 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  - Vicenç Torra
PY  - 2015/06
DA  - 2015/06
TI  - On the selection of m for Fuzzy c-Means
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 1571
EP  - 1577
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.224
DO  - 10.2991/ifsa-eusflat-15.2015.224
ID  - Torra2015/06
ER  -