Sparse linear discriminant analysis in structured covariates space.
Sandra E. SafoQi LongPublished in: Stat. Anal. Data Min. (2019)
Keyphrases
- linear discriminant analysis
- null space
- discriminant analysis
- principal component analysis
- dimensionality reduction
- face recognition
- small sample size
- dimension reduction
- feature extraction
- low dimensional
- high dimensional data
- discriminant features
- feature space
- sample size
- fisher criterion
- class separability
- lower dimensional
- high dimensional
- support vector
- support vector machine svm
- input space
- principal components
- subspace methods
- supervised dimensionality reduction
- computer vision
- fisher discriminant analysis
- sparse coding
- data points
- pattern recognition
- theoretical guarantees
- discriminative information
- singular value decomposition
- sparse representation
- neural network
- generalized discriminant analysis