Keyphrases
- dimensionality reduction
- kernel pca
- linear dimensionality reduction
- data representation
- high dimensional
- low dimensional
- high dimensional feature space
- principal component analysis
- pattern recognition
- feature space
- high dimensional data
- pattern recognition and machine learning
- feature extraction
- dimensionality reduction methods
- high dimensionality
- feature selection
- nonlinear manifold
- linear projection
- subspace learning
- input space
- principal components
- random projections
- pattern classification
- dimension reduction
- data points
- data sets
- manifold learning
- linear discriminant analysis
- graph embedding
- nonlinear equations
- structure preserving
- diffusion maps
- multiscale
- face recognition
- image processing