Reference : Efficiently approximating Markov tree bagging for high-dimensional density estimation
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/96741
Efficiently approximating Markov tree bagging for high-dimensional density estimation
English
Schnitzler, François mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
ammar, sourour [ > > ]
leray, philippe [ > > ]
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-2011
Machine Learning and Knowledge Discovery in Databases, Part III
Gunopulos, Dimitrios
Hofmann, Thomas
Malerba, Donato
Vazirgiannis, Michalis
Springer-Verlag
LNAI 6913
113-128
Yes
No
International
978-3-642-23807-9
Berlin, Heidelberg
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
from 05-09-2011 to 09-09-2011
Prof. A. Likas
Prof. Y. Theodoridis
Athens
Greece
[en] bayesian networks ; Markov trees ; mixture of trees ; bagging ; bootstrap ; Chow-Liu algorithm
[en] We consider algorithms for generating Mixtures of Bagged Markov Trees, for density estimation. In problems defined over many variables and when few observations are available, those mixtures generally outperform a single Markov tree maximizing the data likelihood, but are far more expensive to compute. In this paper, we describe new algorithms for approximating such models, with the aim of speeding up learning without sacrificing accuracy. More specifically, we propose to use a filtering step obtained as a by-product from computing a first Markov tree, so as to avoid considering poor candidate edges in the subsequently generated trees. We compare these algorithms (on synthetic data sets) to Mixtures of Bagged Markov Trees, as well as to a single Markov tree derived by the classical Chow-Liu algorithm and to a recently proposed randomized scheme used for building tree mixtures.
Systèmes et Modélisation
Fonds pour la formation à la Recherche dans l'Industrie et dans l'Agriculture (Communauté française de Belgique) - FRIA ; Biomagnet IUAP network of the Belgian Science Policy Office ; Pascal2 network of excellence of the EC
Researchers
http://hdl.handle.net/2268/96741
10.1007/978-3-642-23808-6_8
http://www.springerlink.com/content/97100k1308156219/
The original publication is available at www.springerlink.com

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