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Discrete Component Analysis

Wray Buntine and Aleks Jakulin (2006) Discrete Component Analysis. In: Lecture Notes in Computer Science. Volume 3940 / 2006. Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers. Springer-Verlag, pp. 1-33.

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    This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-negative matrix factorisation and latent Dirichlet allocation. The main families of algorithms discussed are a variational approximation, Gibbs sampling, and Rao-Blackwellised Gibbs sampling. Applications are presented for voting records from the United States Senate for 2003, and for the Reuters-21578 newswire collection.

    Item Type: Book Section
    Keywords: discrete component analysis, dimension reduction, clustering, principal component analysis, independent component analysis
    Language of Content: English
    Related URLs:
    URLURL Type
    http://dx.doi.org/10.1007/11752790_1Alternative location
    http://arxiv.org/abs/math.ST/0604410Alternative location
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Divisions: Faculty of Computer and Information Science > Other
    Item ID: 207
    Date Deposited: 21 Jul 2006
    Last Modified: 13 Aug 2011 00:32
    URI: http://eprints.fri.uni-lj.si/id/eprint/207

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