Title :
Simultaneous approach to principal component analysis and fuzzy clustering with missing values
Author :
Honda, Katsuhiro ; Sugiura, Nobukazu ; Ichihashi, Hidetomo
Author_Institution :
Graduate Sch. of Eng., Osaka Prefectural Univ., Sakai, Japan
Abstract :
In this paper, we propose a method for partitioning incomplete data including missing values into several fuzzy clusters using local principal components. The novel method is an extension of Fuzzy c-Varieties clustering. Numerical example shows that the method provides a tool for interpretation on the local structures of a database
Keywords :
fuzzy logic; pattern clustering; principal component analysis; database; fuzzy c-varieties clustering; fuzzy clustering; local principal components; missing values; principal component analysis; simultaneous approach; Data engineering; Data mining; Databases; Least squares approximation; Least squares methods; Maximum likelihood estimation; Principal component analysis; Prototypes; Vectors; Yield estimation;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.943827
