A comparison of structural distance measures for causal Bayesian network models

de Jongh, Martijn and Druzdzel, Marek J (2009) A comparison of structural distance measures for causal Bayesian network models. In: Recent Advances in Intelligent Information Systems, Challenging Problems of Science, Computer Science series. Academic Publishing House EXIT, Warsaw, Poland, 443 - 456. ISBN 9788360434598

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Abstract

We compare measures of structural distance between both, Bayesian networks Aand equivalence classes of Bayesian networks. The main application of these measures is in learning algorithms, where typically the interest is in how accurately a gold standard structure is retrieved by a learning algorithm. Structural distance measures can be especially useful when looking for causal structures. We discuss desirable properties of measures, review existing measures, and show some of our empirical findings concerning the performance of these metrics in practice.

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Details

Item Type:	Book Section
Status:	Published
Creators/Authors:	Creators Email Pitt Username ORCID de Jongh, Martijn Druzdzel, Marek J marek@sis.pitt.edu DRUZDZEL 0000-0002-7598-2286
Date:	2009
Date Type:	Publication
Publisher:	Academic Publishing House EXIT
Place of Publication:	Warsaw, Poland
Page Range:	443 - 456
Institution:	University of Pittsburgh
Schools and Programs:	School of Information Sciences > Information Science
Refereed:	Yes
ISBN:	9788360434598
Title of Book:	Recent Advances in Intelligent Information Systems, Challenging Problems of Science, Computer Science series
Editors:	Editors Email Pitt Username ORCID Klopotek, Mieczyslaw UNSPECIFIED UNSPECIFIED UNSPECIFIED Przepiorkowski, Adam UNSPECIFIED UNSPECIFIED UNSPECIFIED Wierzchon, Slawomir T UNSPECIFIED UNSPECIFIED UNSPECIFIED Trojanowski, Krzysztof UNSPECIFIED UNSPECIFIED UNSPECIFIED
Date Deposited:	12 Jul 2011 14:08
Last Modified:	31 Jul 2020 18:59
URI:	http://d-scholarship.pitt.edu/id/eprint/6011

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