DocumentCode :
2004312
Title :
Independence based clustering
Author :
Nishigaki, Takahiro ; Onoda, Takashi
Author_Institution :
Dept. of Comput. Intell. & Syst. Sci., Tokyo Inst. of Technol., Yokohama, Japan
fYear :
2012
fDate :
20-24 Nov. 2012
Firstpage :
386
Lastpage :
390
Abstract :
Existing clustering methods focus on the similarity of data within the cluster. Therefore, distance and independence between clusters were not taken into account. However, users expect that the data within a cluster are similar, and data in different clusters are well separated or independent from each other. In this paper, we propose a clustering method where data within a cluster are similar, and data between clusters are highly independent. We show the results of experiments using benchmark data. And we carried out a survey with high school students.
Keywords :
pattern clustering; benchmark data; data similarity; high school students; independence based clustering; clustering; independent component analysis; k-means;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-2742-8
Type :
conf
DOI :
10.1109/SCIS-ISIS.2012.6505162
Filename :
6505162
Link To Document :
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