PAM, a nearest shrunken centroid method (NSC), is a popular classification method for high-dimensional data. ALP and AHP are NSC algorithms that were proposed to improve upon PAM. The NSC methods base their classification rules on shrunken centroids, in practice the amount of shrinkage is estimated minimizing the overall cross-validated (CV) error rate.