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Boolean Factor Analysis by the Expectation-Maximization Algorithm
- 1.0347803 - ÚI 2011 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
Frolov, A. A. - Polyakov, P.Y. - Húsek, Dušan
Boolean Factor Analysis by the Expectation-Maximization Algorithm.
Proceedings of COMPSTAT 2010. Heidelberg: Physica Verlag, 2010 - (Lechevallier, Y.; Saporta, G.), s. 1039-1046. ISBN 978-3-7908-2603-6.
[COMPSTAT 2010. International Conference on Computational Statistics /19./. Paris (FR), 22.08.2010-27.08.2010]
Grant CEP: GA MŠMT(CZ) 1M0567; GA ČR GAP202/10/0262; GA ČR GA205/09/1079
Výzkumný záměr: CEZ:AV0Z10300504
Klíčová slova: boolean factor analysis * generative model * information gain * efficiency measure
Kód oboru RIV: IN - Informatika
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.
Trvalý link: http://hdl.handle.net/11104/0188494
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