Reference : Mixtures of Bagged Markov Tree Ensembles
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/131217
Mixtures of Bagged Markov Tree Ensembles
English
Schnitzler, François mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Sep-2012
Proceedings of the 6th European Workshop on Probabilistic Graphical Models
Cano Utrera, Andrès
Gómez-Olmedo, Manuel
Nielsen, Thomas
283-290
Yes
No
International
Sixth European Workshop on Probabilistic Graphical Models
from 19-09-2012 to 21-09-2012
Granada
Spain
[en] Bayesian networks ; Markov trees ; Perturb and Combine ; density estimation ; Chow-Liu algorithm ; Mixture of trees ; EM algorithm ; Variance reduction
[en] Markov trees, a probabilistic graphical model for density estimation, can be expanded in the form of a weighted average of Markov Trees. Learning these mixtures or ensembles from observations can be performed to reduce the bias or the variance of the estimated model. We propose a new combination of both, where the upper level seeks to reduce bias while the lower level seeks to reduce variance. This algorithm is evaluated empirically on datasets generated from a mixture of Markov trees and from other synthetic densities.
systems and modelling
Fonds pour la formation à la Recherche dans l'Industrie et dans l'Agriculture (Communauté française de Belgique) - FRIA
Researchers
http://hdl.handle.net/2268/131217

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