DocumentCode
3424364
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
fYear
2009
fDate
17-19 Aug. 2009
Firstpage
148
Lastpage
153
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location
Nanchang
Print_ISBN
978-1-4244-4830-2
Type
conf
DOI
10.1109/GRC.2009.5255142
Filename
5255142
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