On sparse linear discriminant analysis algorithm for high-dimensional data classification.
Michael K. NgLi-Zhi LiaoLei-Hong ZhangPublished in: Numer. Linear Algebra Appl. (2011)
Keyphrases
- high dimensional data
- linear discriminant analysis
- dimension reduction
- dimensionality reduction
- small sample size
- support vector machine svm
- subspace clustering
- high dimensionality
- high dimensional
- discriminant analysis
- qr decomposition
- low dimensional
- dimensional data
- face recognition
- supervised dimensionality reduction
- feature extraction
- learning algorithm
- null space
- support vector
- nearest neighbor
- fisher criterion
- input data
- feature space
- sparse representation
- data points
- data analysis
- principal components
- similarity search
- locally linear embedding
- machine learning
- scatter matrix
- subspace methods
- lower dimensional
- low rank
- input space
- distance function