Empirical comparison of tree ensemble variable importance measures

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Empirical comparison of tree ensemble variable importance measures

Tree ensembles are becoming well-established as popular and powerful data modelling techniques. Tree ensemble models are essentially black box models, although their individual members may not be, and with their growing popularity, interest in the interpretation of tree ensemble models has also grow...

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Bibliographic Details
Main Authors:	Auret, L., Aldrich, Chris
Format:	Journal Article
Published:	ELSEVIER 2011
Subjects:	Decision trees - Variable importance - Ensemble learning - Random forests - Fault identification - Boosted trees - Conditional inference forests
Online Access:	http://hdl.handle.net/20.500.11937/47469

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