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Approximation of Data by Decomposable Belief Models
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SYSNO ASEP 0350718 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Approximation of Data by Decomposable Belief Models Author(s) Jiroušek, Radim (UTIA-B) ORCID Source Title Information Processing and Management of Uncertainty in Knowledge-Based Systems (Part I), I. - Heidelberg : Springer, 2010 / Hüllermeier Eyke ; Kruse Rudolf ; Hoffmann Frank - ISBN 978-3-642-14057-0 Pages s. 40-49 Number of pages 10 s. Publication form www - www Action Information Processing and Management of Uncertainty in Knowledge-Based Systems Event date 28.06.2010-02.07.2010 VEvent location Dortmund Country DE - Germany Event type WRD Language eng - English Country DE - Germany Keywords Discrete belief functions ; Dempster-Shafer theory ; graphical model Subject RIV IN - Informatics, Computer Science R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GA201/09/1891 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation The paper defines the counterpart of decomposable models within Dempster-Shafer theory of evidence and illustrates their efficiency on the problem of approximation of a sample distribution for a data file with missing values Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2011
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