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Boolean Factor Analysis by the Expectation-Maximization Algorithm
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SYSNO ASEP 0347803 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Boolean Factor Analysis by the Expectation-Maximization Algorithm Author(s) Frolov, A. A. (RU)
Polyakov, P.Y. (RU)
Húsek, Dušan (UIVT-O) RID, SAI, ORCIDSource Title Proceedings of COMPSTAT 2010. - Heidelberg : Physica Verlag, 2010 / Lechevallier Y ; Saporta G. - ISBN 978-3-7908-2603-6 Pages s. 1039-1046 Number of pages 8 s. Publication form flash disk - flash disk Action COMPSTAT 2010. International Conference on Computational Statistics /19./ Event date 22.08.2010-27.08.2010 VEvent location Paris Country FR - France Event type WRD Language eng - English Country DE - Germany Keywords boolean factor analysis ; generative model ; information gain ; efficiency measure Subject RIV IN - Informatics, Computer Science R&D Projects 1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GAP202/10/0262 GA ČR - Czech Science Foundation (CSF) GA205/09/1079 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10300504 - UIVT-O (2005-2011) Annotation Compared are e ciencies of two methods for Boolean factor analysis based on expectation-maximization technique. First one is Maximal Causes Analysis proposed by Lucke and Sahani (2008). Second one is Expectation-Maximization Boolean Factor Analysis, introduced here. Last method is strictly based on the general Boolean factor analysis generative model. Comparison is based on so called bars problem benchmark (Foldiak, 1990). Further informational theoretic measure of Boolean factor analysis e ciency is developed. Then it is shown that the e ciency of our Expectation-Maximization Boolean Factor Analysis method is higher then Maximal Causes Analysis in Boolean factor analysis model parameters entirety. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2011
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