Latent and observable variables: Difference between revisions

Revision as of 14:36, 18 February 2006

Revision as of 02:15, 2 April 2006

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One advantage of using latent variables is that it [[Dimensionality reduction|reduces the dimensionality]] of data. A large number of observable variables can be aggregated to represent an underlying concept, making it easier for human beings to understand and assimilate information. At the same time, the latent variables are the link between observable ("sub-symbolic") data in the real world, and symbolic data in the modeled world.

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[[Category:Social sciences]]

[[Category:Bayesian networks]]