liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Scalable, efficient and correct learning of Markov boundaries under the faithfulness assumption
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology. (ADIT)
Center for Genomics and Bioinformatics, Karolinska Institutet, Sweden.
Linköping University, Department of Physics, Chemistry and Biology, Computational Biology. Linköping University, The Institute of Technology.
2005 (English)In: Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 8th European Conference, ECSQARU 2005, Barcelona, Spain, July 6-8, 2005. Proceedings / [ed] Lluís Godo, Springer Berlin/Heidelberg, 2005, Vol. 3571, 136-147 p.Chapter in book (Refereed)
Abstract [en]

We propose an algorithm for learning the Markov boundary of a random variable from data without having to learn a complete Bayesian network. The algorithm is correct under the faithfulness assumption, scalable and data efficient. The last two properties are important because we aim to apply the algorithm to identify the minimal set of random variables that is relevant for probabilistic classification in databases with many random variables but few instances. We report experiments with synthetic and real databases with 37, 441 and 139352 random variables showing that the algorithm performs satisfactorily.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2005. Vol. 3571, 136-147 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 3571
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 3571
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-48160DOI: 10.1007/11518655_13ISBN: 3-540-27326-3ISBN: 978-3-540-27326-4ISBN: e-978-3-540-31888-0OAI: diva2:269056
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2013-10-15Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textfind book at a swedish library/hitta boken i ett svenskt bibliotek

Search in DiVA

By author/editor
Peña, Jose M.Tegnér, Jesper
By organisation
Database and information techniquesThe Institute of TechnologyComputational Biology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 56 hits
ReferencesLink to record
Permanent link

Direct link