"In order to assess the accuracy of the calibration model and
to avoid overfitting, validation procedures have to be applied; a
calibration model without validation is nonsense. Leverage correction
is an equation based procedure to estimate the prediction
accuracy without performing any prediction, and is to be avoided
at all times because it always leads to overoptimistic estimates.
In leave-one-out cross validation, one sample is removed from
the dataset, and a calibration model is constructed for the remaining
subset. The removed samples are then used to calculate the
prediction residual. The process is repeated with other subsets
until every sample has been left out once, and in the end the
variance of all prediction residuals is estimated. In multifold
cross validation, a well-defined number of samples (‘segment’)
are left out instead of one. In internal validation, the dataset
is split into a calibration and a validation set. The calibration
model is constructed using the calibration set, and the prediction
residuals are then calculated by applying the calibration
model to the validation set. In external validation, the validation
dataset is independent, and is, for example, obtained from
a different orchard or different season. Although leverage correction
should not be used, it is still the default cross validation
method in the widely used Unscrambler chemometrics software
(http://www.camo.com)."
(Postharvest Biology and Technology 46 (2007) 99–118
Review
Nondestructive measurement of fruit and vegetable quality
by means of NIR spectroscopy: A review
Bart M. Nicolai ,, Katrien Beullens, Els Bobelyn, Ann Peirs,
Wouter Saeys, Karen I. Theron, Jeroen Lammertyn)
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