Literature DB >> 10226186

On cross validation for model selection.

I Rivals1, L Personnaz.   

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.

Mesh:

Year:  1999        PMID: 10226186     DOI: 10.1162/089976699300016476

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  3 in total

1.  An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.

Authors:  Guillermin Agüero-Chapin; Aminael Sánchez-Rodríguez; Pedro I Hidalgo-Yanes; Yunierkis Pérez-Castillo; Reinaldo Molina-Ruiz; Kathleen Marchal; Vítor Vasconcelos; Agostinho Antunes
Journal:  PLoS One       Date:  2011-10-26       Impact factor: 3.240

2.  Exploring the adenylation domain repertoire of nonribosomal peptide synthetases using an ensemble of sequence-search methods.

Authors:  Guillermin Agüero-Chapin; Reinaldo Molina-Ruiz; Emanuel Maldonado; Gustavo de la Riva; Aminael Sánchez-Rodríguez; Vitor Vasconcelos; Agostinho Antunes
Journal:  PLoS One       Date:  2013-07-16       Impact factor: 3.240

3.  Confidence limits, error bars and method comparison in molecular modeling. Part 2: comparing methods.

Authors:  A Nicholls
Journal:  J Comput Aided Mol Des       Date:  2016-03-04       Impact factor: 3.686

  3 in total

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