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 includes:
- 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
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).