Fuzzy principal component analysis for fuzzy data

Author

Yabuuchi, Yoshiyuki ; Watada, Junzo ; Nakamori, Yoshiteru

Author_Institution

Dept. of Ind. Manage., Osaka Inst. of Technol., Japan

Volume

2

fYear

1997

fDate

1-5 Jul 1997

Firstpage

1127

Abstract

A fuzzy concept is employed to construct a principal component model which can deal with fuzziness, vagueness or possibility, which is called fuzzy principal component analysis for fuzzy data. The fuzzy principal component analysis analyzes the possibility of fuzzy data. The fuzzy principal component analysis for fuzzy data has three formulations according the portions which the possibilities included in fuzzy data are embodied: (1) an eigenvalue, (2) an eigenvector and (3) both eigenvalue and eigenvector. In this paper, we discuss only the first formulation that an eigenvalue is employed to deal with fuzziness of data. The principal component analysis for fuzzy data is employed in this paper to analyze the features of information technology industry. In this analysis, the financial ratio is employed as an index. We evaluate the possibility of a company activity in the information technology industry

Keywords

corporate modelling; covariance matrices; eigenvalues and eigenfunctions; fuzzy set theory; information industry; linear programming; possibility theory; statistical analysis; company activity; eigenvalue; financial ratio; fuzziness; fuzzy data; fuzzy principal component analysis; information technology industry; possibility; vagueness; Data analysis; Eigenvalues and eigenfunctions; Electronic mail; Fuzzy systems; Information analysis; Information technology; Mathematical model; Mathematics; Principal component analysis; Technology management;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on

Conference_Location

Barcelona

Print_ISBN

0-7803-3796-4

Type

conf

DOI

10.1109/FUZZY.1997.622867

Filename

622867