Title :
On fuzzy c-means clustering for uncertain data using quadratic regularization of penalty vectors
Author :
Endo, Yuta ; Hamasuna, Yukihiro ; Kanzawa, Yuchi ; Miyamoto, Sadaaki
Author_Institution :
Dept. of Risk Eng., Univeristy of Tsukuba, Tsukuba, Japan
Abstract :
In recent years, data from many natural and social phenomena are accumulated into huge databases in the world wide network of computers. Thus, advanced data analysis techniques to get valuable knowledge from data using computing power of today are required. Clustering is one of the unsupervised classification technique of the data analysis and both of hard and fuzzy c-means clusterings are the most typical technique of clustering.
Keywords :
data analysis; fuzzy set theory; optimisation; pattern classification; pattern clustering; vectors; data analysis; fuzzy c-means clustering; penalty vectors; quadratic regularization; unsupervised classification technique; Clustering algorithms; Computer networks; Data analysis; Data engineering; Databases; Extraterrestrial measurements; Fuzzy sets; Pattern analysis; Power engineering computing; Uncertainty; fuzzy c-means clustering; penalty vector; quadratic regularization; tolerance; uncertain data;
Conference_Titel :
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location :
Nanchang
Print_ISBN :
978-1-4244-4830-2
DOI :
10.1109/GRC.2009.5255142
