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The models were validated using the full cross validation technique, in order to determine the optimal number of latent variables and to detect the outlier samples.
Validation of models was done using full cross validation (CV), CV-analysis of variance [27] and in some cases prediction of model independent samples.
PCA was performed with full cross validation and mean centering.
The chemometric approach composed of principal component analysis (PCA) and partial least squares regression (PLS) performed with full cross validation to classify the maturity of the cheese.
Full cross validation is an evaluation tool to check calibration models, based on systematically removing samples in the model and testing the performance of the model using the remaining data set.
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Both the PCA and PLS models were validated using the full cross-validation method.
We also trained a regression tree with full cross-validation.
At the calibration stage, coefficient of determination for full cross-validation (R2) of ≥0.70 was obtained for CEC, mc, LL, PI, LS, COLE and VS.
We have performed a full cross-validation of this clinical Femina data collection against the routinely collected data of the Medical Birth Registry of Norway to validate the estimates of reduced mortality in the total population.
The hold-out full cross-validation coefficient of determination (r2)≥0.8 was obtained for the liquid limit (LL), linear shrinkage (LS), coefficient of linear extensibility (COLE), air-dried moisture content, (W) and cation exchange capacity (CEC).
For comparison, PLS models are also constructed by full cross-validation, as well as by using the Kennard Stone and random sampling methods for calibration and validation subset partitioning.
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