Reference : Dual Perturb and Combine Algorithm
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/25740
Dual Perturb and Combine Algorithm
English
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
2001
Proceedings of AISTATS 2001, Eighth International Workshop on Artificial Intelligence and Statistics
196-201
Yes
No
International
Key-West, Florida
Eighth International Workshop on Artificial Intelligence and Statistics
January 2001
Key-West
USA
[en] Machine Learning
[en] In this paper, a dual perturb and combine algorithm is proposed which consists in producing the perturbed predictions at the prediction stage using only one model. To this end, the attribute vector of a test case is perturbed several times by an additive random noise, the model is applied to each of these perturbed vectors and the resulting predictions are aggregated. An analytical version of this algorithm is described in the context of decision tree induction. From experiments on several datasets, it appears that this simple algorithm yields significant improvements on several problems, sometimes comparable to those obtained with bagging. When combined with decision tree bagging, this algorithm also improves accuracy in many problems.
http://hdl.handle.net/2268/25740
http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2001/Geu01

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