<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper deals with the problem of discovering fuzzy clusters with optimal number of elements in heuristic possibilistic clustering. The relational clustering procedure using a parameter that controls cluster sizes is considered and a technique for detecting the optimal number of elements in fuzzy clusters is proposed. The effectiveness of the proposed technique is illustrated through numerical examples. Experimental results are discussed and some preliminary conclusions are formulated.</p></abstract>

The paper deals with the problem of discovering fuzzy clusters with optimal number of elements in heuristic possibilistic clustering. The relational clustering procedure using a parameter that controls cluster sizes is considered and a technique for detecting the optimal number of elements in fuzzy clusters is proposed. The effectiveness of the proposed technique is illustrated through numerical examples. Experimental results are discussed and some preliminary conclusions are formulated.

Heuristic possibilistic clustering for detecting optimal number of elements in fuzzy clusters

Department of Software Information Technology, Belarusian State University of Informatics and Radio-Electronics, P. Brovka St. 6, 220013 Minsk, Belarus

Foundations of Computing and Decision Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The paper deals with the problem of discovering fuzzy clusters with optimal number of elements in heuristic possibilistic clustering. The relational clustering...

Heuristic possibilistic clustering for detecting optimal number of elements in fuzzy clusters

Online veröffentlicht: 31. März 2016

Seitenbereich: 45 - 76

Eingereicht: 24. März 2015

Akzeptiert: 20. Jan. 2016

DOI: https://doi.org/10.1515/fcds-2016-0003

Schlüsselwörter
possibilistic clustering, fuzzy cluster, allotment, cluster size, cluster validity

© 2016 Dmitri A. Viattchenin, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Heuristic possibilistic clustering for detecting optimal number of elements in fuzzy clusters

Online veröffentlicht: 31. März 2016

Seitenbereich: 45 - 76

Eingereicht: 24. März 2015

Akzeptiert: 20. Jan. 2016

DOI: https://doi.org/10.1515/fcds-2016-0003

Schlüsselwörterpossibilistic clustering, fuzzy cluster, allotment, cluster size, cluster validity

© 2016 Dmitri A. Viattchenin, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
possibilistic clustering, fuzzy cluster, allotment, cluster size, cluster validity