NDLI: Weighted principal component analysis for interval-valued data based on fuzzy clustering

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Weighted principal component analysis for interval-valued data based on fuzzy clustering

Content Provider	IEEE Xplore Digital Library
Author	Sato-Ilic, M.
Copyright Year	2003
Description	Author affiliation: Inst. of Policy & Planning Sci., Tsukuba Univ., Japan (Sato-Ilic, M.)
Abstract	This paper proposes a weighted principal component analysis (WPCA) for interval-valued data using the result of fuzzy clustering. In this method, we introduce two data structures which are classification structure and principal component structure. One of them is used for weights and the other is used for the analysis of itself. So, we can reduce the risk of a wrong assumption of the introduced data structure, comparing the conventional method which assumes only one data structure on the observation.
Sponsorship	Syst., Man & Cybernetics Soc. IEEE
Starting Page	4476
Ending Page	4482
File Size	389783
Page Count	7
File Format	PDF
ISBN	0780379527
ISSN	1062922X
DOI	10.1109/ICSMC.2003.1245689
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Principal component analysis Data analysis Data structures TV Watches Frequency Electronic mail Uncertainty Electronics packaging Arithmetic
Content Type	Text
Resource Type	Article

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