Partial least squares discriminant analysis (PLS-DA) is an adaptation of PLS regression methods to the problem of supervised1 clustering. It has seen extensive use in the analysis of multivariate datasets, such as that derived from NMR-based metabolomics.
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1D 1H NMR is a common technique applied to metabolomic studies, being well suited to untargeted analysis of complex biofluids. It has been successfully applied to the classification and diagnosis of a number of diseases including [ref].