Modified linear discriminant analysis using block covariance matrix in high-dimensional data.
Jin Hyun NamDonguk KimPublished in: Commun. Stat. Simul. Comput. (2017)
Keyphrases
- linear discriminant analysis
- covariance matrix
- high dimensional data
- principal component analysis
- dimensionality reduction
- low dimensional
- discriminant analysis
- dimension reduction
- covariance matrices
- principal components analysis
- high dimensional
- nearest neighbor
- data sets
- data points
- data analysis
- small sample size
- input space
- high dimensionality
- gaussian mixture
- subspace clustering
- null space
- original data
- sample size
- similarity search
- principal components
- manifold learning
- lower dimensional
- feature space
- dimensionality reduction methods
- sparse representation
- input data
- euclidean distance
- face recognition
- feature extraction
- objective function
- low rank
- face images
- image processing
- independent component analysis
- subspace methods
- vector space
- neural network
- subspace learning
- metric learning