Paper Info
Title
Hybrid objective function of Fuzzy c-Varieties and cross-shape fuzzy cluster extraction
Abstract
This paper proposes an FCM-type clustering method for capturing cross-shape fuzzy clusters in multi-dimensional data spaces. The proposed objective function is a combination of Fuzzy c-Varieties (FCV) and cross-shape cluster extraction in 2-D space, which is an extended linear fuzzy clustering model with local coordinate rotation. FCV is responsible for finding 2-D planes, on which cross-shape prototypes exist. Each prototypical cross is estimated on the FCV prototypes. Fuzzy memberships are updated using a combined clustering criterion of distances between data samples and FCV prototypes and measures for linear clustering on the FCV prototypes with local coordinate rotation.
Year
DOI
Venue
2011
10.1109/FUZZY.2011.6007508
Fuzzy Systems
Keywords
Field
DocType
data handling,fuzzy set theory,pattern clustering,statistical analysis,2D plane finding,2D space,FCM-type clustering method,FCV prototype,cross shape fuzzy cluster extraction,cross shape prototype,data sample,extended linear fuzzy clustering model,fuzzy c-variety,fuzzy memberships,hybrid objective function,linear clustering,local coordinate rotation,multidimensional data space,co-clustering,collaborative filtering,principal component analysis
Fuzzy clustering,Fuzzy classification,Computer science,Fuzzy set,FLAME clustering,Artificial intelligence,Fuzzy control system,Biclustering,Cluster analysis,Mathematical optimization,Pattern recognition,Fuzzy logic,Machine learning
Conference
ISSN
ISBN
Citations 
1098-7584 E-ISBN : 978-1-4244-7316-8
978-1-4244-7316-8
0
PageRank 
References 
Authors
0.34
8
4
Name
Order
Citations
PageRank
Daisuke Yoshida100.34
K. Honda214512.73
Notsu, A.3134.23
Hidetomo Ichihashi437072.85