Scaled PCA: A New Approach to Dimension Reduction.
Dashan HuangFuwei JiangKunpeng LiGuoshi TongGuofu ZhouPublished in: Manag. Sci. (2022)
Keyphrases
- dimension reduction
- principal component analysis
- principle component analysis
- dimension reduction methods
- dimensionality reduction
- feature extraction
- linear discriminant analysis
- random projections
- low dimensional
- high dimensional problems
- singular value decomposition
- principal components
- manifold learning
- discriminant analysis
- feature space
- face recognition
- independent component analysis
- high dimensional
- covariance matrix
- feature selection
- high dimensional data
- feature subspace
- partial least squares
- discriminative information
- face images
- manifold embedding
- nonlinear manifold
- high dimensional data analysis
- machine learning
- dimensionality reduction methods
- principal components analysis
- subspace learning
- data sets
- kernel pca
- preprocessing step
- qr decomposition
- high dimensionality
- input image
- sparse metric learning