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Supervised PCA

This code accompanies our work:

@article{ritchie2020supervised,
title={Supervised PCA: A Multiobjective Approach},
author={Ritchie, Alexander and Balzano, Laura and Kessler, Daniel and Sripada, Chandra S and Scott, Clayton},
journal={arXiv preprint arXiv:2011.05309},
year={2020}
}

There are several helper files. The callable files are:

  1. lspca_sub.m - supervised pca with the least squares loss function; for regression; uses substitution for \beta in place of alternating updates
  2. lspca_MLE_sub.m - same as above; uses maximum likelihood updates for tuning parameter \lambda
  3. lrpca.m - supervised pca with the logistic loss function; for classification
  4. lrpca_MLE.m same as above; uses maximum likelihood updates for tuning parameter \lambda
  5. the four files above prepended with 'k' - kernelized versions of those algorithms

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  • MATLAB 100.0%