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Variable selection through CART

Marie Sauvé 1 Christine Tuleau 1
1 SELECT - Model selection in statistical learning
LMO - Laboratoire de Mathématiques d'Orsay, Inria Saclay - Ile de France
Abstract : This paper deals with variable selection in the regression or binary classification frameworks. It proposes an automatic and exhaustive procedure which relies on the use of the CART algorithm and on model selection via penalization. This work, of theoretical nature, aims at determining adequate penalties, i.e. penalties which allow to get "oracle type inequalities" justifying the performances of the proposed procedure. A simulation study completes the theoretical results.
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Contributor : Rapport de Recherche Inria Connect in order to contact the contributor
Submitted on : Tuesday, May 23, 2006 - 4:48:28 PM
Last modification on : Wednesday, April 20, 2022 - 3:37:41 AM
Long-term archiving on: : Tuesday, February 22, 2011 - 11:54:12 AM


  • HAL Id : inria-00071350, version 1


Marie Sauvé, Christine Tuleau. Variable selection through CART. [Research Report] RR-5912, INRIA. 2006. ⟨inria-00071350⟩



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