Least Squares Canonical Correlation Analysis
Liang Sun, Shuiwang Ji, and Jieping Ye
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
- Kernel CCA.
- Least squares.
- Kernel least squares.
- LS_CCA, the equivalent least squares formulation for
- KLS_CCA, the equivalent kernel least squares
formulation for kernel CCA.
- Orthonormalized partial least squares (OPLS).
LSCCA is distributed for non-commercial use only.
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).
If you have any comments or questions, please feel free to contact Liang Sun
or Jieping Ye (firstname.lastname@example.org).