On fuzzy c-means and membership based clustering
2015 (English)In: Advances in Computational Intelligence: 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12, 2015: Proceedings, Part I / [ed] Ignacio Rojas, Gonzalo Joya & Andreu Catala, Springer, 2015, 597-607 p.Conference paper (Refereed)
Fuzzyc" role="presentation">c-means is one of the most well known fuzzy clustering algorithms. It is usually solved using an iterative algorithm. This algorithm does not ensure that the solution is the global optimum. In this paper we study the distribution of values of the objective function of fuzzyc" role="presentation">c
We also propose a new fuzzy clustering method related to fuzzy c-means. The method presumes that the shape of the membership function is known and can be calculated from the cluster centers, which are the only results of the clustering algorihm.
Place, publisher, year, edition, pages
Springer, 2015. 597-607 p.
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9094
Fuzzy c-means, Membership based clustering with fuzzy c-means membership
IdentifiersURN: urn:nbn:se:his:diva-13357DOI: 10.1007/978-3-319-19258-1_49ISI: 000363763800049ScopusID: 2-s2.0-84937459963ISBN: 978-3-319-19257-4 (print)ISBN: 978-3-319-19258-1 (electronic)OAI: oai:DiVA.org:his-13357DiVA: diva2:1071373
13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12, 2015