Hybrid objective function of Fuzzy c-Varieties and cross-shape fuzzy cluster extraction

Author

Yoshida, Daisuke ; Honda, Katsuhiro ; Notsu, Akira ; Ichihashi, Hidetomo

Author_Institution

Dept. of Comput. Sci. & Intell. Syst., Osaka Prefecture Univ., Sakai, Japan

fYear

2011

fDate

27-30 June 2011

Firstpage

799

Lastpage

803

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.

Keywords

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; Clustering algorithms; Data mining; Fuzzy systems; Principal component analysis; Prototypes; Shape; Vectors; co-clustering; collaborative filtering; principal component analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (FUZZ), 2011 IEEE International Conference on

Conference_Location

Taipei

ISSN

1098-7584

Print_ISBN

978-1-4244-7315-1

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZY.2011.6007508

Filename

6007508