Sparse principal component regression via singular value decomposition approach.
Shuichi KawanoPublished in: Adv. Data Anal. Classif. (2021)
Keyphrases
- singular value decomposition
- principal component regression
- low rank approximation
- partial least squares
- dimension reduction
- low rank matrices
- singular vectors
- principal components
- low rank matrix
- singular values
- least squares
- principal component analysis
- dimensionality reduction
- latent semantic indexing
- random projections
- low rank
- high dimensional
- feature space
- kernel space
- learning algorithm
- computer vision
- training data
- machine learning
- discriminant analysis
- unsupervised learning
- data points