Our approach enjoys many advantages including flexibility, general penalties, easy interpretation of results, and fast computation in high-dimensional settings.

Aug 1, 2013 · We introduce a framework for Regularized PLS by solving a relaxation of the SIMPLS optimization problem with penalties on the PLS loadings ...

Nov 19, 2012 · Strimmer, Partial least squares: a versatile tool for the analysis of high-dimensional genomic data, Brief Bioinform 8(1) (2007), 32. 3K. Lê Cao ...

A framework for Regularized PLS is introduced by solving a relaxation of the SIMPLS optimization problem with penalties on the PLS loadings vectors, ...

Regularized Partial Least Squares with an Application to NMR Spectroscopy. Stat Anal Data Min. 2013 Aug 01; 6(4):302-314. View in: PubMed.

We introduce a framework for Regularized PLS by solving a relaxation of the SIMPLS optimization problem with penalties on the PLS loadings vectors. Our approach ...

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Research has been carried out to determine the potential of partial least squares (PLS) modeling of mid-infrared (IR) spectra of crude oils combined with ...

Dec 7, 2020 · Regularized Partial Least Squares with an Application to NMR Spectroscopy. Stat. Anal. Data Min. 2013, 6, 302– 314, DOI: 10.1002/sam.11169.

Sep 10, 2015 · Results: We propose two PLS extensions called group PLS (gPLS) and sparse gPLS (sgPLS). Our algorithm enables to study the relationship between ...