Boolean Factor Analysis by the Expectation-Maximization Algorithm

Autoři: Dušan Húsek
Rok vydání: 2010
Typ publikace: Konferenční příspěvek (mezinárodní konf.)
Periodikum: Proceedings of COMPSTAT 2010
Projekty: Centrum aplikované kybernetiky
Rozklady matic s binárními a ordinálními daty: teorie, algoritmy, složitost
Metody umělé inteligence v GIS
Bibliografická citace: FROLOV, A. A., POLYAKOV, P.Y., HÚSEK, Dušan. Boolean Factor Analysis by the Expectation-Maximization Algorithm. In: LECHEVALLIER, Y, SAPORTA, G., eds. Proceedings of COMPSTAT 2010. Heidelberg: Physica Verlag, 2010, S. 1039-1046. ISBN 978-3-7908-2603-6.
ID: 347803

Abstrakt

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.