Kernel Entropy Discriminant Analysis for Dimension Reduction.
Aditya MehtaC. Chandra SekharPublished in: PReMI (2017)
Keyphrases
- dimension reduction
- discriminant analysis
- linear discriminant analysis
- kernel discriminant analysis
- principal component analysis
- discriminant subspace
- feature extraction
- feature space
- support vector
- kernel pca
- dimensionality reduction
- face recognition
- high dimensional data
- graph embedding
- partial least squares
- cluster analysis
- low dimensional
- kernel function
- discriminative information
- factor analysis
- fisher discriminant analysis
- manifold learning
- principal components
- support vector machine svm
- subspace learning
- high dimensional
- random projections
- input space
- image processing
- kernel trick
- high dimensionality
- preprocessing
- kernel methods
- pattern recognition
- data sets
- feature selection
- feature vectors
- kernel matrix
- maximum margin
- support vector machine
- object recognition
- singular value decomposition
- semi supervised