LSCCA Package: Least Squares Canonical Correlation Analysis

Liang Sun, Shuiwang Ji, and Jieping Ye


Introduction

LSCCA is a Matlab implementation of the least squares formulation for Canonical Correlation Analysis (CCA).  Several extensions of Least Squares CCA based on regularization are also included, including the sparse CCA formulation using the 1-norm regularization. This package also provides the implementation of CCA, kernel CCA, and Orthonormalized Partial Least Squares (OPLS). Specifically, the LSCCA package includes:

  1. CCA.
  2. Kernel CCA.
  3. Least squares.
  4. Kernel least squares.
  5. LS_CCA, the equivalent least squares formulation for CCA.
  6. KLS_CCA, the equivalent kernel least squares formulation for kernel CCA.
  7. Orthonormalized partial least squares (OPLS).

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LSCCA is distributed for non-commercial use only.


Acknowledgements

The LSCCA software project has been supported by research grants from the National Science Foundation (NSF) under Grant No. IIS-0953662 and the National Geospatial Agency (NGA).

Feedback

If you have any comments or questions, please feel free to contact Liang Sun (sun.liang@asu.edu) or Jieping Ye (jieping.ye@asu.edu).