Feature Extraction and Uncorrelated Discriminant Analysis for High-Dimensional Data.
Wen-Hui YangDao-Qing DaiHong YanPublished in: IEEE Trans. Knowl. Data Eng. (2008)
Keyphrases
- high dimensional data
- discriminant analysis
- linear discriminant analysis
- discriminant vectors
- feature extraction
- dimensionality reduction
- dimension reduction
- low dimensional
- nearest neighbor
- high dimensional
- data sets
- principal component analysis
- data analysis
- data points
- subspace clustering
- manifold learning
- high dimensionality
- original data
- null space
- sparse representation
- fisher criterion
- small sample size
- input space
- face recognition
- scatter matrices
- feature vectors
- fisher discriminant analysis
- kernel principal component analysis
- principal components analysis
- low rank
- subspace learning
- lower dimensional
- preprocessing step
- image classification
- discriminant projection
- dimensional data
- database
- support vector machine svm
- input data
- pattern recognition
- random projections
- knn
- principal components
- neural network
- real world
- image feature extraction
- feature space
- feature selection