title: On cross validation for model selection.
abstract: In response to Zhu and Rower (1996), a recent communication (Goutte, 1997) established that leave-one-out cross validation is not subject to the "no-free-lunch" criticism. Despite this optimistic conclusion, we show here that cross validation has very poor performances for the selection of linear models as compared to classic statistical tests. We conclude that the statistical tests are preferable to cross validation for linear as well as for nonlinear model selection.
authors.affiliation: Laboratoire d'Electronique, Ecole Superieure de Physique et de Chimie Industrielles (ESPCI), 10 rue Vauquelin, 75231, Paris, France. Isabelle.Rivals@espci.fr
authors.forename: I
authors.initials: I
authors.lastname: Rivals
authors.forename: L
authors.initials: L
authors.lastname: Personnaz
mesh_terms: D016014:Linear Models; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D011336:Probability; D015203:Reproducibility of Results