Reference : Some enhancements of decision tree bagging
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/25744
Some enhancements of decision tree bagging
English
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
2000
Proceedings of PKDD 2000, 4th European Conference on Principles of Data Mining and Knowledge Discovery
Springer-Verlag
LNAI 1910
136-147
Yes
No
International
Lyon, France
4th European Conference on Principles of Data Mining and Knowledge Discovery
Lyon
France
[en] machine learning
[en] This paper investigates enhancements of decision tree bagging which mainly aims at improving computation times, but also accuracy. The three questions which are reconsidered are: discretization of continuous attributes, tree pruning, and sampling schemes. A very simple discretization procedure is proposed, resulting in a dramatic speedup without significant decrease in accuracy. Then a new method is proposed to prune an ensemble of trees in a combined fashion, which is significantly more effective than individual pruning. Finally, different resampling schemes are considered leading to different CPU time/accuracy tradeoffs. Combining all these enhancements makes it possible to apply tree bagging to very large datasets, with computational performances similar to single tree induction. Simulations are carried out on two synthetic databases and four real-life datasets.
http://hdl.handle.net/2268/25744
http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2000/Geu00

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