A new approach to the problem of clustering using the fuzzy joint points method
Automatic Control and Computer Sciences, vol.39, no.6, pp.8-17, 2005 (Scopus)
- Publication Type: Article / Article
- Volume: 39 Issue: 6
- Publication Date: 2005
- Journal Name: Automatic Control and Computer Sciences
- Journal Indexes: Scopus
- Page Numbers: pp.8-17
- Keywords: Fuzzy clustering, Fuzzy conical point, Fuzzy joint points (FJP), Fuzzy joint set
- Dokuz Eylül University Affiliated: Yes
Abstract
A new hierarchical approach to the problem of clustering, called the Fuzzy Joint Point, FJP) method is proposed. In the FJP method each element of the clusterized set is considered a fuzzy point of a multidimensional space. The concepts of a fuzzy conical point, fuzzy α-neighborhood, and fuzzy α-joint points are introduced and studies of certain properties relative to these concepts are carried out. The proposed algorithm of the FJP method may be used as a preparatory stage of the Fuzzy c-Means (FCM) algorithm for determining the initial classes and their dimensions and also as an independent clustering algorithm. © 2006 by Allerton Press, Inc.