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
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Status: |
Published |
Creators/Authors: |
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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 |
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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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