Keyphrases
- high dimensional data
- linear discriminant analysis
- random matrix theory
- dimensionality reduction
- discriminant analysis
- correlation matrix
- dimension reduction
- nearest neighbor
- low dimensional
- high dimensional
- small sample size
- data sets
- high dimensionality
- data points
- subspace clustering
- similarity search
- manifold learning
- data analysis
- null space
- original data
- principal components analysis
- principal component analysis
- input data
- low rank
- lower dimensional
- subspace learning
- subspace methods
- covariance matrix
- sparse representation
- singular value decomposition
- scatter matrices
- principal components
- locally linear embedding
- k nearest neighbor