期刊
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
卷 22, 期 6, 页码 395-406出版社
ELSEVIER SCIENCE LONDON
DOI: 10.1016/S0165-9936(03)00607-1
关键词
chance correlation; cross-validation; overfitting; permutation test; variable selection
Different methods of cross-validation are studied for their suitability to guide variable-selection algorithms to yield highly predictive models. It is shown that the commonly applied leave-one-out cross-validation has a strong tendency to overfitting, underestimates the true prediction error, and should not be used without further constraints or further validation. Alternatives to leave-one-out cross-validation and other validation methods are presented. (C) 2003 Published by Elsevier Science B.V.
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