Multi-Label
Dimensionality Reduction
Liang Sun,
Opera Solutions
Shuiwang Ji,
Old Dominion University
Jieping Ye, University
of Michigan
The MLDR (Multi-Label Dimensionality Reduction) package implements many popular dimensionality reduction algorithms, with an emphasis on multi-label dimensionality reduction algorithms. Specifically, MLDR implements the following dimensionality reduction algorithms:
Ø Canonical Correlation Analysis (CCA)
Ø Orthonormalized Partial Least Squares (OPLS)
Ø Hypergraph Spectral Learning (HSL)
Ø Linear Discriminant Analysis (LDA)
Ø The Shared-Subspace Learning Framework (SSL)
MLDR is distributed for non-commercial use only:
If you have any comments or questions, please feel free to contact Liang Sun (sun.liang@asu.edu) or Jieping Ye (jpye@umich.edu).