DocumentCode
1694210
Title
Fuzzy claustering application to marketing data and feature extraction of data
Author
Tomoko, Ninomiya
Author_Institution
Tamagawa Univ.
fYear
2008
Firstpage
1
Lastpage
6
Abstract
Usually, the population of a large marketing dataset is assumed that a mixture of two or more different groups. In this paper, to classify the observations into the group of some different populations, we propose a fuzzy clustering technique that uses an unobserved variable that influences the observed variables. And, we show an effectiveness of the technique to clarify the data structure and to extract the feature.
Keywords
data mining; data structures; feature extraction; fuzzy set theory; marketing data processing; pattern clustering; data feature extraction; data structure; fuzzy clustering; marketing data; marketing dataset; Computer performance; Data analysis; Data mining; Data structures; Educational institutions; Feature extraction; Fuzzy sets; Information technology; Internet; Proposals; Fuzzy clustering; Marketing data; observed Variable; unobserved variable;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Congress, 2008. WAC 2008. World
Conference_Location
Hawaii, HI
Print_ISBN
978-1-889335-38-4
Electronic_ISBN
978-1-889335-37-7
Type
conf
Filename
4698948
Link To Document