MATLAB toolbox for classification by SO-PLS-LDA, MB-PLS-LDA and PLS-LDA
SO-PLS-LDA is a classification method based on the combination of the multi-block SO-PLS regression method and LDA. This toolbox contains MATLAB functions that allow choosing the optimal complexity on the basis of the Måge plot, fitting the SO-PLS-LDA models using different type of cross-validation and then making classification by LDA. The output is a structure that will contain not only the SO-PLS-LDA model, but also the MB-PLS-LDA model built on the same blocks and the PLS-LDA models on the single blocks. For applications and a description of the methods involved see:
Biancolillo,I. Måge,T. Næs, Combining SO-PLS and linear discriminant analysis for multi-block classification. (paper submitted to Chemometrics and Intelligent Laboratory Systems)
The toolbox (zip-file) can be downloaded here
- PLS: Partial Least Squares
- SO-PLS: Sequential Orthogonal-PLS
- PO-PLS: Parallell Orthogonal-PLS
- LDA: Linear Discriminant Analysis
- MB: Multiblock