Abstract
A condition of overtraining a back-propagation neural network exists when excessive model degrees of freedom are used in network training. A CRT color calibration experiment was done to illustrate methods to avoid an overtrained condition in model development. Cross-validation, in which the experimental data are split into parameter-training and independent-test data sets, is advocated. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 122–125, 2002; DOI 10.1002/col.10027
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