Sequential and orthogonalized Covariance Selection (SO-CovSel)
Sequential and orthogonalized Covariance Selection (SO-CovSel) is a recently proposed multi-block algorithm for variable-selection in supervised multi-block modeling (calibration and classification). It takes inspiration from Sequential and Orthogonalized Partial Least Squares regression (SO-PLS) and Covariance selection (CovSel) algorithms.
The details of the SO-CovSel algorithm can be found in the following paper:
A. Biancolillo, F, Marini, J.-M. Roger, SO‐CovSel: A novel method for variable selection in a multiblock framework, J. Chemometr. 34 (2020) e3120.
Download the Matlab functions
SO-CovSel for multi-block regression
SO-CovSel-LDA for multi-block classification