Procrustes Cross-Validation of short datasets in PCA context
2021
Pomerant︠s︡ev, A. L. (Alekseĭ Leonidovich) | Rodionova, Oxana Ye
We suggest using a new tool, Procrustes cross-validation, as an alternative to a regular cross-validation for short datasets where each sample is important and, therefore, cannot be removed in line with the conventional leave-one-out cross-validation procedure. The advantages of the new approach are demonstrated using two real-world examples: the first one contains discrete variables (chemical profiles). The second one is based on continuous data (spectra). The method is implemented in R and Matlab as a small procedure that any analyst can easily use.
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