A Novel LDA Approach for High-Dimensional Data.
Guiyu FengDewen HuMing LiZongtan ZhouPublished in: ICNC (1) (2005)
Keyphrases
- high dimensional data
- linear discriminant analysis
- dimensionality reduction
- dimension reduction
- discriminant analysis
- small sample size
- nearest neighbor
- high dimensional
- low dimensional
- high dimensionality
- high dimensions
- data sets
- subspace clustering
- data points
- original data
- similarity search
- high dimensional spaces
- manifold learning
- lower dimensional
- data analysis
- subspace methods
- sparse representation
- dimensional data
- latent dirichlet allocation
- input space
- low rank
- nonlinear dimensionality reduction
- feature space
- null space
- principal component analysis
- face recognition
- locally linear embedding
- neural network
- scatter matrices
- clustering high dimensional data
- input data
- pattern recognition
- feature extraction
- subspace learning
- topic models
- generative model
- variable weighting