Title :
On the extension of fuzzy k-means algorithms for detection of linear clusters
Author :
Bezdek, J. ; Gunderson, R. ; Ehrlich, R. ; Meloy, T.
Author_Institution :
Utah State University, Logan, Utah
Abstract :
In this note we discuss an extension of the fuzzy ISODATA (or fuzzy k-means) clustering algorithms, which attempt to recognize and compensate for their failure at detection of linear substructure in finite data sets. A numerical example is given to substantiate the proposed extension: and we offer some theoretical conjectures concerning its construction.
Keywords :
Algorithm design and analysis; Clustering algorithms; Data processing; Fuzzy sets; Geology; Mathematics; Partitioning algorithms; Prototypes; Shape; Training data;
Conference_Titel :
Decision and Control including the 17th Symposium on Adaptive Processes, 1978 IEEE Conference on
Conference_Location :
San Diego, CA, USA
DOI :
10.1109/CDC.1978.268155
