Title :
Fuzzy c-means for Fuzzy Hierarchical Clustering
Author_Institution :
IIIA-CSIC, Bellaterra
Abstract :
This paper describes an algorithm for building fuzzy hierarchies. These are hierarchies where the elements can have fuzzy membership to the nodes. The paper presents an approach that mainly follows a bottom-up strategy, and describes the functions needed to operate with fuzzy variables. An example of the application of the approach is also presented
Keywords :
fuzzy set theory; fuzzy systems; hierarchical systems; pattern clustering; bottom-up strategy; fuzzy c-means; fuzzy hierarchical clustering; fuzzy variables; Application software; Clustering algorithms; Clustering methods; Computer vision; Data mining; Data privacy; Data visualization; Fuzzy sets; Partitioning algorithms; Self organizing feature maps;
Conference_Titel :
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location :
Reno, NV
Print_ISBN :
0-7803-9159-4
DOI :
10.1109/FUZZY.2005.1452470
