Mixture of Partial Least Squares Experts - Mix-PLS

Mixture of Partial Least Squares Experts


Updated 6 Mar 2015

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The Mixture of Partial Least Squares Experts (Mix-PLS) is a method suitable for learning in multiple operating modes. In industrial applications, such kind of scenario is very common. Then, the Mix-PLS integrates the partial least squares regression (PLS), a well know method in chemometrics literature and one of the mostly used methods for soft sensors in industry, into the mixture of experts framework, thus deriving the new Mix-PLS regression. It is also suitable for nonlinear regression.
In case of publication of any application of this method, please, cite the original work: Francisco A.A. Souza, Rui Araújo, Mixture of partial least squares experts and application in prediction settings with multiple operating modes, Chemometrics and Intelligent Laboratory Systems, Volume 130, 15 January 2014, Pages 192-202. DOI: http://dx.doi.org/10.1016/j.chemolab.2013.11.006.

More information can be found in my website: www.isr.uc.pt/~fasouza

Cite As

Francisco Alexandre Souza (2023). Mixture of Partial Least Squares Experts - Mix-PLS (https://www.mathworks.com/matlabcentral/fileexchange/45418-mixture-of-partial-least-squares-experts-mix-pls), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

Bug fixes
Added the function that train the Mix-PLS model with a validation data set, according with the following division: (train, validation - to evaluate the quality of parameters given by training, testing).