Reference : Ensembles of extremely randomized trees and some generic applications

	Document type :	Scientific congresses and symposiums : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/2268/13447

Title :	Ensembles of extremely randomized trees and some generic applications
Language :	English
Author, co-author :	Wehenkel, Louis [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
	Ernst, Damien [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
	Geurts, Pierre [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Publication date :	2006
Main document title :	Proceedings of Robust Methods for Power System State Estimation and Load Forecasting
On invitation :	No
Audience :	International
Event name :	Robust Methods for Power System State Estimation and Load Forecasting
Event date :	2006
Event place (city) :	Versailles (RTE Building)
Event country :	France
Keywords :	[en] automatic learning ; robust supervised learning methods ; time-series classification ; learning of optimal control policies
Abstract :	[en] In this paper we present a new tree-based ensemble method called “Extra-Trees”. This algorithm averages predictions of trees obtained by partitioning the inputspace with randomly generated splits, leading to significant improvements of precision, and various algorithmic advantages, in particular reduced computational complexity and scalability. We also discuss two generic applications of this algorithm, namely for time-series classification and for the automatic inference of near-optimal sequential decision policies from experimental data.
Funders :	Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
Target :	Researchers ; Professionals
Permalink :	http://hdl.handle.net/2268/13447

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	Fulltext file(s): File Commentary Version Size Access Open access robust-trees.pdf Publisher postprint 247.79 kB View/Open

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