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