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Title: A possibilistic approach to latent structure analysis for symmetric fuzzy data.
Authors: D'Urso, Pierpaolo
Giordani, Paolo
Keywords: Latent structure analysis
symmetric fuzzy data set
possibilistic approach.
Issue Date: 30-Dec-2003
Abstract: In many situations the available amount of data is huge and can be intractable. When the data set is single valued, latent structure models are recognized techniques, which provide a useful compression of the information. This is done by considering a regression model between observed and unobserved (latent) fuzzy variables. In this paper, an extension of latent structure analysis to deal with fuzzy data is proposed. Our extension follows the possibilistic approach, widely used both in the
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