Sparse principal component regression via singular value decomposition approach.
Shuichi KawanoPublished in: CoRR (2020)
Keyphrases
- singular value decomposition
- principal component regression
- low rank approximation
- low rank matrices
- partial least squares
- principal components
- dimension reduction
- singular vectors
- low rank matrix
- principal component analysis
- singular values
- dimensionality reduction
- least squares
- low rank
- latent semantic indexing
- random projections
- data matrix
- high dimensional
- sparse representation
- kernel space