This paper deals with variable selection in regression and 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 achievement of oracle type inequalities justifying the performance of the proposed procedure. Since the exhaustive procedure cannot be realized when the number of variables is too large, a more practical procedure is also proposed and still theoretically validated. A simulation study completes the theoretical results.
Mots-clés : binary classification, CART, model selection, penalization, regression, variable selection
@article{PS_2014__18__770_0,
author = {Sauve, Marie and Tuleau-Malot, Christine},
title = {Variable selection through {CART}},
journal = {ESAIM: Probability and Statistics},
pages = {770--798},
publisher = {EDP-Sciences},
volume = {18},
year = {2014},
doi = {10.1051/ps/2014006},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ps/2014006/}
}
TY - JOUR AU - Sauve, Marie AU - Tuleau-Malot, Christine TI - Variable selection through CART JO - ESAIM: Probability and Statistics PY - 2014 SP - 770 EP - 798 VL - 18 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ps/2014006/ DO - 10.1051/ps/2014006 LA - en ID - PS_2014__18__770_0 ER -
Sauve, Marie; Tuleau-Malot, Christine. Variable selection through CART. ESAIM: Probability and Statistics, Tome 18 (2014), pp. 770-798. doi : 10.1051/ps/2014006. http://www.numdam.org/articles/10.1051/ps/2014006/
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